Final Report Project No. LA 32 - SysTem for Analysis, Research and

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Final Report Project No. LA 32 - SysTem for Analysis, Research and

Vulnerability and Adaptation of
Estuarine Systems of the Río de la
Plata
A Final Report Submitted to Assessments of Impacts and
Adaptations to Climate Change (AIACC), Project No. LA 32
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Vulnerability and Adaptation of Estuarine
Systems of the Río de la Plata
A Final Report Submitted to Assessments of Impacts and
Adaptations to Climate Change (AIACC), Project No. LA 32
Submitted by Gustavo J. Nagy
Instituto de Biología, Departamento de Ecología, Sección Oceanología,
Facultad de Ciencias, UdelaR, Montevideo, Uruguay
2006
Published by
The International START Secretariat
2000 Florida Avenue, NW
Washington, DC 20009 USA
www.start.org
Table of Contents
About AIACC………………………..…………………………………………..............page ix
Summary Project Information………………………………………………………….page x
Executive Summary………………….………………………………………….………page xii
1
Introduction...............................................................................................................................................................1
1.1
1.2
1.3
1.4
2
Characterization of Current Climate and Scenarios of Future Climate Change ....................................4
2.1
2.2
2.2.1
2.2.2
2.2.3
2.2.4
2.3
2.4
2.4.1
2.4.2
2.5
2.5.1
2.5.2
2.5.3
2.5.4
2.5.5
2.5.6
2.6
3
PROBLEM ...........................................................................................................................................................1
PRIMARY OBJECTIVES AND EXPECTED OUTPUTS OF THE PROJECT BY 2001 UPDATED TO 2004. ....................2
THE MAIN EXPECTED OUTPUTS OF THE PROJECT WERE:...................................................................................2
THE EXPOSED ANALYZED UNITS WERE: ............................................................................................................3
ACTIVITIES CONDUCTED ON CURRENT CLIMATE BASELINES ..........................................................................4
SCIENTIFIC METHODS AND DATA .....................................................................................................................4
Empirica l / Statisca l. ..................................................................................................................................4
GCMs.................................................................................................................................................................4
Statistical and dynamical downscaling experiments. .........................................................................4
Overall framework and methods ..............................................................................................................5
SELECTED CLIMATE MODELS ............................................................................................................................6
INDICATORS AND PROXY V ARIABLES ...............................................................................................................6
Environment (weather/water quality/ecosystem/coasta l zone). ....................................................6
Coasta l fishery system ................................................................................................................................6
RESULTS OF LONG-TERM CLIMATIC, HYDROLOGIC AND OCEANOGRAPHIC TRENDS ....................................7
Temperature....................................................................................................................................................7
Precipita tions.................................................................................................................................................7
River flows......................................................................................................................................................8
Sea level pressure..........................................................................................................................................9
Sea level rise ............................................................................................................................................... 10
Sa linity ......................................................................................................................................................... 10
SOCIO-ECONOMIC FUTURES ........................................................................................................................... 11
Impacts and Vulnerability .................................................................................................................................. 13
3.1
3.1.1
3.1.2
3.1.3
3.1.4
3.1.5
3.2
3.2.1
3.2.2
3.2.3
3.2.4
3.2.5
3.2.6
3.2.7
3.2.8
3.2.9
DESCRIPTION OF THE STUDIED SYSTEM AND VULNERABLE SECTORS ........................................................... 13
Location and geomorphology of the Rio de la Plata river estuary ................................................ 13
Meteorology, climatology, hydrology and hydrography ................................................................ 13
Estuarine waters dynamics, ecosystem and services .......................................................................... 14
4. Estuarine front (EF) ................................................................................................................................ 15
Wa ter column structure and associated biogeochemical processes................................................. 17
IMPACTS, VULNERABILITY AND ECONOMIC SCENARIOS OF COASTAL FISHERIES ...................................... 19
Goal ................................................................................................................................................................ 19
Problem.......................................................................................................................................................... 19
Artisanal fishery ....................................................................................................................................... 20
Industria l fishery (coasta l zone untill 50 m depth; not analyzed in detail here) ..................... 20
Risk and uncerta inty: Sources, environmenta l and management conditions................................ 20
Pathways of response of human and natural systems to global environmental change. .......... 21
Sensitivity and vulnerability of coasta l fisheries............................................................................ 23
Integrated climatic, economic and enviromenta l assessment, scenarios and models ................. 25
Key findings................................................................................................................................................. 30
3.3
IMPACTS, VULNERABILITY AND COPING CAPACITY OF TROPHIC STATE CHANGES (TSC) ........................ 30
3.3.1 Goal ................................................................................................................................................................ 30
3.3.2 Problem.......................................................................................................................................................... 30
3.3.3 Trophic state................................................................................................................................................ 30
3.3.4 The overload of nutrients: An environmental change on a global scale ........................................ 31
3.3.5 Eutroph ication and organic metabolism (P-R) .................................................................................... 31
3.3.6 Susceptibility .............................................................................................................................................. 32
3.3.7 Eutroph ication pressures and troph ic status in the Rio de la Plata .............................................. 33
3.3.8 Indicators of susceptibility, impact and vulnerability .................................................................... 34
3.3.9 Causes and symtpoms of eutroph ication in the Rio de la Pla ta ..................................................... 35
3.3.10 Harmful alga l blooms (HABs) .............................................................................................................. 35
3.3.11 Coping capacity and resiliency to troph ic state changes ............................................................... 38
3.3.12 Susceptibility in microtida l systems................................................................................................... 39
3.3.13 Summary of determinant factors on the susceptibility to expres symptoms of eutroph ication
and current troph ic state scenario of the Rio de la Pla ta. ............................................................. 40
3.3.14 Reflections on the use and application of trophic indicators in the Rio de la Plata ............... 41
3.3.15 Oxic status and vulnerability of the fish h abita t ........................................................................... 42
3.4
SEA LEVEL RISE AND COASTAL VULNERABILITY OF THE WESTERN COAST OF MONTEVIDEO ................... 42
3.4.1 Introduction .................................................................................................................................................. 42
3.4.2 Dynamical factors th a t increase vulnerability to SLR are: ............................................................ 43
3.4.3 Factors of vulnerability ............................................................................................................................ 43
3.5
SANTA LUCÍA RIVER ESTUARY ...................................................................................................................... 46
3.5.1 Hydrology .................................................................................................................................................... 46
3.5.2 Trophic state................................................................................................................................................ 48
3.5.3 Scenario for 2050 ......................................................................................................................................... 49
4
Adaptation .............................................................................................................................................................. 51
4.1
4.2
4.3
4.4
4.5
4.5.1
4.5.2
4.5.3
4.5.4
4.6
5
ACTIVITIES CONDUCTED ................................................................................................................................. 51
WHAT IS ADAPTION? ...................................................................................................................................... 51
HOW DOES ADAPTATION OCCUR?................................................................................................................. 51
SCIENTIFIC METHODS AND DATA .................................................................................................................. 51
RESULTS .......................................................................................................................................................... 51
Migration adapta tion strategy of artisanal fisheries..................................................................... 51
Industria l fisheries .................................................................................................................................... 52
Integrated Coasta l Zone Management and Adaptation Control Information System.............. 52
Scenarios of adapta tion and susta inability ........................................................................................ 53
CONCLUSIONS ................................................................................................................................................. 55
Expected future climatic and environmental scenarios, impacts and vulnerability............................ 56
5.1
IMPLICATIONS FOR ESTUARINE BIOCOMPLEXITY. ........................................................................................ 56
5.1.1 Temperature ................................................................................................................................................. 56
5.1.2 Climate change implications after about 2040. .................................................................................. 56
5.1.3 Climate change implications.................................................................................................................. 56
5.2 FUTURE REGIONAL CLIMATE SCENARIOS AND EXPECTED ENVIRONMENTAL IMPACTS AND VULNERABILITY. 57
5.2.1 Regional climate scenarios for Southeastern South America. ........................................................ 57
5.2.2 Statistical and dynamical downscaling experiments. ...................................................................... 60
5.2.3 Some conjectures about future climatic scenarios and associated environmenta l vulnerability
and impacts. ................................................................................................................................................. 60
6
Overall concluding remarks .............................................................................................................................. 66
7
Capacity Building Outcomes and Remaining Needs.................................................................................. 67
7.1
7.2
CAPACITY BUILDING ...................................................................................................................................... 67
REMAINING NEEDS ......................................................................................................................................... 67
8
National Communications, Science-Policy Linkages and Stakeholder engagement ......................... 69
9
Policy implications and Future Directions..................................................................................................... 70
10
Published and Submitted Papers...................................................................................................................... 71
11
References............................................................................................................................................................... 72
List of Tables
Table 1: Current (2000) and future (2050) national socioeconomic scenarios (SRES A-1, top) and B-2 (below)
(modified from data from the UCC; Sención, 2002; Nagy et al., 2002-). ............................................................ 12
Table 2: a- Average fronts loci down-river from Colonia (DRC), ranges of salinity, nitrates (uM) and chl-a (ug/l),
and 3-months running mean of extreme QV (103 m3/s),% QU, and b- extreme fronts loci (MTF, SMF,
MMF) (from Nagy et al., submitted to JASR). ...................................................................................................... 17
Table 3: Evolution of mean dissolved oxygen and nutrients in the botton layer of the water column (depth > 10 m;
salinity > 20, winds < 8 m/s) from mixing (by wind) to prolonged stratification conditions (modified from
Nagy et al., 2000; Nagy et al., 2002c)..................................................................................................................... 18
Table 4: Assessment of the Vulnerability of the Coastal Fishermen Community. (Modified from Nagy et al., 2003
and Norbis et al., 2004). Unweighted total Index of Vulnerability (IV) = 2.2 (scale 1-3). ................................. 25
Table 5: Economic estimation of fishing unit (from Sención, 2003)............................................................................. 28
Table 6: Loads, concentrations and ratios of typical nutrients, and degree of expression (1=light, 2= moderate, 3=
high) of trophic indicators (C,B,O, HAB) in the Rio de la Plata: fluvial, frontal, Canal Oriental and Marine
(modified from Nagy 2002 and 2005). ................................................................................................................... 34
Table 7: Aggregated impact matrix of HABs (both fesh-and estuarine waters) in the Uruguayan coastal zone of the
Rio de la Plata for the period 1991-2000 (from Ferrari and Nagy, 2003). ........................................................... 36
Table 8: Aggregated impact index of HABs for the Rio de la Plata (1991-2000; from Ferrari and Nagy, 2003)...... 37
Table 9: Weighted aggregated impact index of HABs (IPET) for each species and sector in the Northern coast of
the Rio de la Plata (1991-2000; from Ferrari and Nagy, 2003)............................................................................. 37
Table 10: Coping capacity, resiliency, ecosystem state and impacts as a function of river flow and wind thresholds
(Y: A*X* functions); (based upon data from Norbis, 1995; Nagy et al., 2001; Nagy et al., 2002c; Nagy et al.,
submitted). ................................................................................................................................................................ 38
Table 11: Characteristics of the classification of coastal plain estuaries (EPA, 2001) and it’s appliccation to the
study of trophic state of the Rio de la Plata. ........................................................................................................... 40
Table 12: Nitrogen load, rate of export, mixing status and subclinal oxic status (OK, Anoxia-A, Hypoxia-H) of
subsystems of the Rio de la Plata and other stratified estuarine systems (based on EPA, 2001; Nagy et al.,
2002c)........................................................................................................................................................................ 41
Table 13: Synthesis of previous cualitative assessments of the vulnerability of people, sectors, and systems in the
western coast of Montevideo (from Kokot et al., 2004, based on Saizar, 1997; Nicholls and Mimura, 1998;
EcoPlata, 2000; OECD, 2004; UCC, 2004). .......................................................................................................... 43
Table 14: Coastal vulnerability matrix for the western coast of Montevideo (from Kokot et al., 2004). ................... 44
Table 15: Daily river heights (DRH) during ENSO (October/December) and ENSO +1 (January/ February) years
(1979-2003) in the middle Santa Lucia Basin (modified from Caffera et al., 2004)........................................... 48
Table 16: Global accumulative, systemic and ENSO-related climatic and environmental changes in the Rio de la
Plata basin and Estuary. ........................................................................................................................................... 64
Table 17: Past, current and future scenarios of trophic state expressed by Cyanobacterial Harmful Algal Blooms
(C-HABs). Six periods are defined, from baseline (1) to a plausible future scenario for 2020-50 (6) (modified
from López and Nagy, 2005)................................................................................................................................... 65
List of Figures
Fig. 1: Vulnerability, Adaptation and Responses: assessments (from SEI, 2001)............................................. xiv
Fig. 2: Estuarine Front location under different ENSO conditions: a) Strong La Niña event (1999-2000), b)
Typical c) Moderate El Niño (winter 1987) d) strong El Niño 1997-1998 / 2002 – 2003; c + d:
estuarine plume (modified from Nagy et al., 2002b)........................................................................................2
Fig. 3: Multi-level indicator of Vulnerability to Climate Variability and Change for coastal systems of the
Rio de la Plata (modified from Ponce et al., 2002, adapted from Moss et al., 1999)...................................5
Fig. 4: Evolution of yearly air temperature at El Prado, Montevideo (1883 – 2003). From
Bidegain et al.,
(2005). ..........................................................................................................................................................................7
Fig. 5: Evolution of yearly air temperature at Montevideo (1974-2003). From Nagy et al, (2004)....................8
Fig. 6: Evolution of yearly precipitations at El Prado, Montevideo (1883 – 2003). From ...................................8
Fig. 7: River Uruguay flow at Salto from 1921 to 2003. From Bidegain et al., (2005). .........................................9
Fig. 8: River Paraná flow from 1940 to 2000. From Nagy et al., (2002c). ...............................................................9
Fig. 9: Relationship between monthly SST 3.4 and river flows of Rivers Uruguay (black) and Paraná (red)
from .............................................................................................................................................................................9
Fig. 10: Evolution of Sea Level Pressure at El Prado, Montevideo (1901 – 2001). ............................................. 10
Fig. 11: Sea Level Rise at Montevideo for the period 1902 – 2000 (Pshennikov et al., 2003)........................... 10
Fig. 12: Evolution of yearly mean salinity at Montevideo (discotinuous time-series 1906-2000). ................ 11
Fig. 13: Rio de la Plata location and cited regions.................................................................................................... 14
Fig. 14: Coupled model diagram of the processes and feedbacks affecting the hydrologic cycle and
coastal ecosystems of the Rio de la Plata Basin and coastal ecosystems (from Berbery et al., 2003)... 15
Fig. 15: Estuarine Front (EF) of the Rio de la Plata (SeaWIFS image) ......................................................................... 16
Fig. 16: Sketch of the river flow corridors and front-lines of the Rio de la Plata. Distance down-river from
Colonia is shown in Km.. The estuarine front includes the MTF and SMF (Nagy et al., submitted to
JASR). ....................................................................................................................................................................... 17
Fig. 17: Frontal zone of the Rio de la Plata and location of sites of fishermen settlements (white). Urban
areas of the metropolitan Montevideo city (pink) (from Hernández and Rossi, 2002).......................... 19
Fig. 18: Monthly relationships between ENSO SST 3,4 vs Uruguay River flow (left) and Uruguay River
flow vs salinity off Montevideo for the period January 1998 – Decemeber 2000 (from Nagy et al.,
2002b) ....................................................................................................................................................................... 20
Fig. 19: Typical artisanal fishing unit of Pajas Blancas CFS settlement (from Sención, 2003). ....................... 21
Fig. 20: Pathways of response of fishermen (human system) and eutrophication (natural system) to
combined climate change, ENSO-related variability, and human drivers (modified from Nagy et
al., 2003). .................................................................................................................................................................. 22
Fig. 21: Causal diagram loop of the coastal fishery system livelihood vulnerability (from Ponce, 2004) ... 23
Fig. 22: Long-term fishing activity and net income (From Nagy et al., 2003). ................................................... 25
Fig. 23: Evolution of salinity at Pajas Blancas (October 2002 - May 2004). During 2002 salinity was zero
during the fishing period whereas during 2003 it was normal (from Norbis et al., 2004). ................... 26
Fig. 24: Extreme seaward location of the estuarine front (red and yellow lines during El Niño event
(September-October 2002) (from Severov et al., 2004). ................................................................................. 27
Fig. 25: Frequency of wind favorable and unfavorable conditions and non-fishing days for the period
September 2001 – March 2003 (from Nagy et al., 2003). ............................................................................... 27
Fig. 26: Clusters of number of fishing sorties, capture (Nb of boxes), and minimum and maximum Nb of
boxes during the fishing period 1998-1999. ..................................................................................................... 28
Fig. 27: Fishing activity and productivity scenario of Pajas Blancas coastal fishermen community (from
Norbis et al., 2004). ................................................................................................................................................ 29
Fig. 28: Physical control factors of the susceptibility of estuarine systems to express symptoms of
trophic state change (Nagy 2003)....................................................................................................................... 33
Fig. 29: d-PSI Framework (modifed from Nagy, 2003). ......................................................................................... 35
Fig. 30: Conceptual coping range of trophic state changes (Δ N, P, N/P, buoyancy, flushing time, HABs,
Chl-a) as a function of river flow variability (modified from Nagy, 2003)............................................... 39
Fig. 31: Sea level rise in Montevideo during the period 1971-2000 (from Nagy et al., 2004a)........................ 42
Fig. 32: Coastal vulnerability of western Montevideo and Santa Lucia coastal zone. ..................................... 45
Fig. 33: Main Santa Lucía River basin, southern Uruguay, and the estuarine front......................................... 46
Fig. 34: Santa Lucía River yearly discharge (1979-2003)......................................................................................... 47
Fig. 35: Monthly average precipitations at Florida in the middle Santa Lucia basin. ...................................... 47
Fig. 36: Level of discrimination of river water height in the Santa Lucia middle basin during October and
February for the period 1979-2003 (from Caffera et al., 2004). .................................................................... 48
Fig. 37: Evolution of salinity and chlorophyll-a at Santiago Vázquez (estuary, left) and Delta del Tigre
(river-estuary boundary, right) from October 2002 to May 2004 (from Caffera et al., 2004). ............... 49
Fig. 38: Environmental, economic and technological adaptive management conditions of industrial
fishery (from Norbis, 2003).................................................................................................................................. 52
Fig. 39: Hierarchical procedure of the adaption control information system - ACIS (modified from
Norbis, 2003)........................................................................................................................................................... 53
Fig. 40: Figure Comparison between observed Vs modeled total accumulated boxes.................................... 54
Fig. 41: Fishing scenarios: Capture (log of boxes) as a function of sortied days. .............................................. 55
Fig. 42: Future changes (2050) in Sea level pressure (above), and temperature (below) for RPB.................. 58
Fig. 43: Future scenarios for precipitation (SRES-A2a) for 2050 (above) and 2080 (below). ........................... 59
About AIACC
Assessments of Impacts and Adaptations to Climate Change (AIACC) enhances capabilities in the
developing world for responding to climate change by building scientific and technical capacity,
advancing scientific knowledge, and linking scientific and policy communities. These activities are
supporting the work of the United Nations Framework Convention on Climate Change (UNFCCC)
by adding to the knowledge and expertise that are needed for national communications of parties
to the Convention.
Twenty-four regional assessments have been conducted under AIACC in Africa, Asia, Latin
America and small island states of the Caribbean, Indian and Pacific Oceans. The regional
assessments include investigations of climate change risks and adaptation options for agriculture,
grazing lands, water resources, ecological systems, biodiversity, coastal settlements, food security,
livelihoods, and human health.
The regional assessments were executed over the period 2002-2005 by multidisciplinary, multiinstitutional regional teams of investigators. The teams, selected through merit review of submitted
proposals, were supported by the AIACC project with funding, technical assistance, mentoring and
training. The network of AIACC regional teams also assisted each other through collaborations to
share methods, data, climate change scenarios and expertise. More than 340 scientists, experts and
students from 150 institutions in 50 developing and 12 developed countries participated in the
project.
The findings, methods and recommendations of the regional assessments are documented in the
AIACC Final Reports series, as well as in numerous peer-reviewed and other publications. This
report is one report in the series.
AIACC, a project of the Global Environment Facility (GEF), is implemented by the United Nations
Environment Programme (UNEP) and managed by the Global Change SysTem for Analysis,
Research and Training (START) and the Third World Academy of Sciences (TWAS). The project
concept and proposal was developed in collaboration with the Intergovernmental Panel on Climate
Change (IPCC), which chairs the project steering committee. The primary funding for the project is
provided by a grant from the GEF. In addition, AIACC receives funding from the Canadian
International Development Agency, the U.S. Agency for International Development, the U.S.
Environmental Protection Agency, and the Rockefeller Foundation. The developing country
institutions that executed the regional assessments provided substantial in-kind support.
For more information about the AIACC project, and to obtain electronic copies of AIACC Final
Reports and other AIACC publications, please visit our website at www.aiaccproject.org.
ix
Summary Project Information
Regional Assessment Project Title and AIACC Project No.
Vulnerability and Adaptation of Estuarine Systems of the Río de la Plata (LA 32)
Abstract
The Rio de la Plata basin and estuary have been substantially influenced by human
activities in recent decades, and are highly sensitive to climate extremes and changing
precipitation patterns caused by climate change and variability. This project will develop
regional hydroclimatic scenarios and assess impacts and vulnerability to climate change
and variability in socioeconomic and environmental sectors for the Rio de la Plata. The
study will include the development of reference projections (5-30 years) for a range of
climate and non-climate factors to understand ecosystem response and obtain credible
estimates of future impacts on salinity, nutrient-pollution, net ecosystem metabolism,
fisheries resources, and aquatic biodiversity. Research will address a number of
crosscutting factors important for assessing vulnerability, including changes in baseline
socioeconomic conditions and assessment of adaptation costs. In order to orient scientific
efforts toward effective management or policy decisions at the regional or national level,
the project will lay the framework for an Adaptation Control Information System, which
provides information and recommendations for developing anticipatory adaptation
measures. The project team will identify, in consultation with other scientists and policy
makers, which policies are most in need of immediate implementation, and analyze the
costs and benefits of alternative adaptation strategies and current practices.
Administering Institution
Facultad de Ciencias de la Universidad de la República (UdelaR), Iguá 4225, Montevideo,
Uruguay
Participating Stakeholder Institutions
Unit of Climater Change, Ministery of Housing, Planning and Environment, Montevideo,
Uruguay
Unit of Water Quality, Ministery of Housing, Planning and Environment, Montevideo,
Uruguay
Directorate of Water Resources, Ministery of Public Works, Montevideo, Uruguay
Countries of Primary Focus
Uruguay and Argentina
Case Study Areas
Estuarine Waters of the Rio de la Plata and coastal systems of Uruguay
Systems and Sectors Studied
Climate, Biodiversity, Regional Economy
Estuarine Ecosystems, Regional Climate Scenarios and Modeling, Sea Level Rise, Coastal
Zone, Water Resources, Fisheries, Health
Groups Studies
Subsistence Fishermen
x
Sources of Stress and Change
Changes in mean annual/seasonal climate; Precipitations (increase in droughts,
inundations and river floods) ; River Flow; Temperature; Sea Level Pressure; Winds /
Storm Surges; Sea Level (both eustatic and non-eustatic); Other stresses (non-climatic);
Population Growth; Land Use Change; Damming; Nutrient inputs
Project Funding and In-Kind Support
AIACC: US 100,000 grant; Ministery of Housing, Planning and Environment: Project GEFFREPLATA: US 6,250; Facultad de Ciencias In-Kind Support
Investigator(s)
Principal Investigator:
Gustavo J Nagy (Coastal and Estuarine Oceanographer),
Uruguayan, Instituto de Biología, Departamento de Ecología, Sección Oceanología,
Facultad de Ciencias, UdelaR, Montevideo, Uruguay. [email protected] and
[email protected], Departamento de Ecología, Sección Oceanología, Facultad de
Ciencias (FC), Iguá 4225, Montevideo, Uruguay
Other Investigators: Mario Bidegain (Climatologist), Uruguayan, Instituto de Física,
Unidad de Meteorología, FC-UdelaR, Montevideo, Uruguay; Federico Blixen
(Geographer/Climatologist), Uruguayan, Directorate of Meteorology, Uruguay;
Graciela Ferrari (Biological Oceanographer), Uruguayan, Directorate of Aquatic Resources
(DINARA), Montevideo, Uruguay; Ernesto A. Forbes (Oceanographer/Sea Level Rise),
Uruguayan, Directorate of Hydrography and Oceanography, Uruguayan Navy,
Montevideo, Uruguay; Ruben Mario Caffera, Consultant in Severe Meteorological Events,
Environment and Water Resources; Uruguayan, Unidad de Cambio Climático, Ministerio
de Vivienda, Ordenamiento Territorial y Medio Ambiente (MVOTMA), Unidad de Cambio
Climático (UCC). Professor of Meteorology, Graduate Programe, Facultad de Agronomía,
UdelaR.; Carlos M. Martínez (Physical Oceanographer), Uruguayan, Instituto de Biología,
Director, Sección Oceanología, FC- UdelaR, Montevideo, Uruguay. Professor of
Oceanography; Walter Norbis (Fisheries Scientist), Uruguayan, Directorate of Aquatic
Resources (DINARA), Montevideo, Uruguay. Associate Profesor of Fisheries, FC-UdelaR;
Valentina Pshennikov (Meteorologist), Russian, Instituto de Física, Unidad de
Meteorología, FC-UdelaR, Montevideo, Uruguay. Assistant Professor of Meteorology;
Gustavo Sención (Economist, MSc), Uruguayan,
Facultad de Ciencias Sociales
(Departamento de Economía) and FC-UdelaR, Montevideo, Uruguay. Associate Professor
of Environmental Economics and Natural Resources; Dimitri N. Severov (Physical
Oceanographer), Russian, Sección Oceanología, Facultad de Ciencias, UdelaR, Montevideo,
Uruguay. Professor of Oceanography; Roberto Torres (Civil Engineer/Water Resources),
Uruguayan, Directorate of Water Resources, Montevideo, Uruguay;
xi
Executive Summary
Research Problem (as thought by 2001 and updated to 2004).
The Third Assessment Report (TAR) of the IPCC (2001), referred to as TAR, identified two main
environmental problems in South America: Land Use Changes and ENSO variability. The Rio de la
Plata basin (RPB) and estuary (RP) have been substantially influenced by human activities in recent
decades and are highly sensitive to climate extremes and changing precipitation patterns. The
Paraná-Uruguay system river water discharge increased by ~30% since 1961 with the consequent
increase in river flow (QV) and decrease in salinity (Nagy et al. 1997, 2002).
The RP is susceptible to develop symptoms of eutrophication (Nagy et al., 2002c). As a result of the
changing climatic and nonclimate conditions over the past fifty years both the natural susceptibility
(vulnerability) to flush and dilute nutrients and the development of symptoms of eutrophication
(impact) increased. Within the frontal zone or estuarine front (EF) such processes like nutrient
removal, in situ production of organic matter (CH20), and denitrification are estimated to be high
(Nagy, 2000). The main symptoms of eutrophication are an increase of organic matter (CH20)
”expressed” as increased algal biomass (B) and production (P), oxygen stress, and Harmful Algal
Blooms (HABs).
The increase in river flow variability vary both the location and structure of the Estuarine Front,
affecting the sites of reproduction and catch of fishes. Thus, coastal fisheries are impacted because
of the changing accessibility of the fishing area (i.e. 1987-1988 and 1997-1999).
Primary objectives and expected outputs of the project updated to
2004.
Overall goal of the project was: i) to assess vulnerability and impacts of/on the estuarine waters
(hydrology and ecosystem), coast and resources of the RP and ii) to plan adaptation strategies for
coastal fisheries (Adaptive Control Information System-ACIS) in order to cope with climate
variability and change, weather conditions and nonclimate scenarios. The key questions to be
addressed were:
•
How sensitive is the system to Climate Variability and Change?
•
Is eutrophication related to Climate Change and Variability?
•
Is the coastal fishery system sustainable under increased river flow variability?
•
Will the coastal zone be heavily impacted over the next few decades?
The secondary questions to be answered were:
•
How would an increase of River flow (QV ) and Nutrient input (NI) affect trophic state and
symptoms of eutrophication (i.e. oxygen stress and HABs), especially along the Canal
Oriental?
•
Is the frontal zone role as a site for reproduction, nursery and feeding of fisheries resources
modified by short- and long-term hydroclimatic variability?
•
How do the consecutive occurrence of hydroclimatic extremes (i.e. the 1998-2000 period),
affect the adaptive capacity of the estuarine ecosystems?
The exposed analyzed units were:
i) the estuarine frontal zone and ii) the Santa Lucía river lower basin, estuary and associated coastal
zone. We focused on the understanding of ecosystem response in order to obtain credible estimates
of future vulnerability and impacts on:
•
trophic status changes (increase in symptoms of eutrophication),
xii
•
coastal fisheries and associated livelihood vulnerability, and
•
water resources, trophic state changes (TSC) and sea-level rise (SLR) in the Santa Lucia
river lower basin and estuary (SLRE).
Time horizons considered were from the past 30 years and present through 2030 / 2050 / 2080.
Approach
The overall approach taken in this multisectoral research has consisted of combining several
methods. We can divide them into three main ones:
•
Empirical / Statistical;
•
Global Circulation Models (GCM) and
•
Downscaling techiniques.
Empirical / Statiscal. We reconstructed climatic, enviromental, hydrological and oceanographic timeseries from available data and proxy variables.
Global Circulation Models. We selected seven available runs from IPCC Distribution Data Center,
using socioeconomic SRES-A2 and B2 forcing scenarios. We have compared sea level pressure
(SLP), surface air temperature and precipitation from the models, against observed climate fields,
trying to estimate regional performance of the control simulations (1961 – 1990 baseline). The
comparison between the monthly and annual SLP fields shows that only four models (HADCM3,
CSIRO-mk2, ECHAM4, GFDL-R30) have an acceptable agreement with the observed SLP field. All
scenarios underestimate precipitation. The future climate change scenarios, for precipitation and
temperature were constructed for 2020, 2050 and 2080s.
Statistical and dynamical downscaling experiments. In order to generate precipitation and temperature
daily time series based on future climate change scenarios from the GCMs we selected the both
statistical and dynamical techniques for downscaling to bridge the spatial and temporal resolution
gaps between climate models and vulnerability assessments requirements. We made use of
statistical downscaling technique trough the SDSM model (Wilby et al., 2001). This model showed to
be a valuable tool to represent some of the characteristics that existed in the regional precipitation
data. Another tool used to generate future high resolution scenarios over Southeastern South
America was PRECIS (Hadley Center’s regional climate modeling system).
Overall framework for vulnerability and adaptation
The overall Framework of this research is the second generation assessment (SEI, 2001, Figure 1).
xiii
Fig. 1: Vulnerability, Adaptation and Responses: assessments (from SEI, 2001).
Scientific findings and questions
Main climatic changes in the RPB are the increase in ENSO variability and precipitation (≥ 20%),
southward displacement of the Atlantic subtropical high pressure circulation-SAHP and changes in
frequencies of the prevailing winds; increase in air and water temperatures (≥ 0.8 ºC), as well as
changes in runoff, soil moisture and the Pantanal’s extent (Díaz et al., 1998; Camilloni and Barros,
2000; Escobar et al., 2004; Bidegain et al., 2004; Liebmann et al., 2004).
Climate Trends
We have updated climate, hydrologic and oceanographic yearly long-term trends up to 2000 / 2003
(temperature, precipitation, sea level pressure, river flows, sea level rise, salinity).
Coastal Fishery System
Goal: To assess overall vulnerability of the Coastal Fishery System (CFS) in the Estuarine Front of
the Rio de la Plata to cope with Global Environmental Change.
Problem: An artisanal fleet exploit fisheries a few miles off the Uruguayan coast in the estuarine
front (EF) of the Rio de la Plata. Both, the observations and the economic scenario suggest: In case of
an increase in climatic constraints only performant and better adapted fishermen should be able to
remain within the frontal zone fishing area.
Trophic State and Eutrophication: Even if nutrient inputs to the Rio de la Plata are well below the
figures for developed countries, they are higher than they were by 1950. Summarizing:
Eutrophication in the Rio de la Plata system can be thought of as a syndrome (a suite of symptoms)
that change with the seasons, years and decades, showing an increasing trend of pressure and state
indicators since the mid 1940s, and a shift during the 1970s and 1980s. Natural processes must have
been accelerated due to the increase in hydroclimatic means and extremes that led to an increase in
soil erosion and diffuse sources of nutrients. These processes, combined with human activities such
as damming, which have indirectly altered the trophic status by modifying the physical
environment (e.g., residence time, local warming), determine that the increase in nutrient load over
xiv
the last five decades, even if it was well below the figures for developed countries, has altered the
natural trophic status background and/or stimulated the development of new symptoms, whose
drivers are expected to increase (since 1990) in the next few decades (López and Nagy 2005).
Sea Level Rise and coastal vulnerability of the Western Coast of Montevideo: The western coastline of
Montevideo (~80 km including fishermen settlements, Santa Lucía river estuary and mouth,
beaches and wetlands) was previously defined by several qualitative assessments as one of the
most vulnerable of the country to sea level rise-SLR (Saizar, 1997; Nagy et al., 2005). The solely
long-term tide-gauge record in Uruguay is located within this coastal section (Punta Lobos). We
used a quantitative index of vulnerability and objectivley classified this coastal section as highly
vulnerable.
Santa Lucia River Estuary and Coastal Zone: Interannual variability of Santa Lucia river flow (QSL) is
strongly ENSO-related in the middle basin from August to February. Such as a relationship with
ENSO was not expected because previous works indicated that it’s signal was relatively weak in
Southern Uruguay (Bidegain and Caffera, 1989). The evolution of trophic state changes (TSC)
showed a strong relationship with the increase in freshwater (October 2002 to May 2003) which
enhanced physical controls on TS other than temperature. This control blocked the expression of
symptoms of eutrophication (i.e., chlorophyll-a) when salinity was <1 in the estuarine zone. Once
both QV and QSL were within their normal range, salinity increased to 4-7 as well as chl-a did up to
eutrophic levels.
Summarizing, hydrology, which is partially ENSO-controlled, is a strong physical control of
biogeochemical processes and TSC of Santa Lucia river estuary. River flow fluctuations induce
enviromental within this system and in the adjacent coastal waters of the EF of the RP.
Future Climate Scenarios and environmental vulnerability: We selected seven available runs from
IPCC Distribution Data Center, using socioeconomic SRES-A2 and B2 forcing scenarios. We have
compared sea level pressure (SLP), surface air temperature and precipitation from the models,
against observed climate fields, trying to estimate regional performance of the control simulations
(baseline climate scenarios). The comparison between the monthly and annual SLP fields shows
that only four models (HADCM3, CSIRO-mk2, ECHAM4, GFDL-R30) have an acceptable
agreement with the observed SLP field and are able to represent the position and intensity of the
pressure systems and the annual cycle. In all cases, precipitation is largely underestimated within
the Río de la Plata basin. The comparison between the monthly and annual temperature fields
shows that in general all the models have an acceptable agreement with the observed fields.
The future climate change scenarios for precipitation and temperature, over Southern cone of South
America were constructed for 2020, 2050 and 2080s.
Statistical and dynamical downscaling experiments: In order to generate precipitation and temperature
daily time series based on future climate change scenarios from the Global Climate Models (GCMs)
we selected the both statistical and dynamical techniques for downscaling to bridge the spatial and
temporal resolution gaps between climate models and vulnerability assessments requirements. We
made use of statistical downscaling technique trough the SDSM model (Wilby et al., 2001). The
selected predictor variables (taken from NCEP reanalysis) for daily precipitation are sea level
pressure, zonal and meridian wind components at 850 hPa. We selected four locations in
Southeastern South America during the period 1996 – 2001: Buenos Aires, Santa Fe, Montevideo
and Salto. SDSM model showed to be a valuable tool and is capable of representing some of the
characteristics that existed in the precipitation data of the temperate region of South America.
Another tool used to generate future high resolution scenarios over Southeastern South America
was PRECIS (Hadley Center’s regional climate modeling system). These scenarios are being
developed at present and will be used in impact, vulnerability and adaptation assessments as well
as in third National Communication to the UNFCC behalf the Unit of Climate Change (Ministry of
Environment).
xv
Some conjectures about plausible climatic and environmental scenarios: Current environmental scenarios
(1971-2003) in the Rio de la Plata basin (RPB) and estuary discussed all along this report are
dominated by the following main stresses:
•
increases in temperature, precipitation, river flows, sea-level rise and onshore winds.
•
increases in population, damming, use of natural resources and export of nutrients.
•
increases in economic activities, land use changes, soil erosion and runoff / infiltration
ratio.
Current climate and future scenarios (time horizon 2020 - 2050) for the RPB and estuary suggest a
change in precipitation, temperature and sea-level rise within the ranges +5% to +20%, +1 to +2°C
and 10-15 cm respectively, whereas during the last few decades these changes have being + 20 to
25% for precipitation, +0.5 to +0.8°C for temperature, 5 cm for SLR, as well as + 25 to 40% for river
flows (QV).
Trends for QVs are very difficult to be estimated because of both the uncertainty of regional human
drivers and because of the varied regional scenarios from different GCMs. Main uncertainty is
related to the understimation of precipitation and the relative amounts of potential and actual
evapotranspiration rates in the future. Under a future scenario (2020-2050) in which streamflow
remains similar or slightly lower (i.e. 0% to -10%), we do not expect a significative increase in
present environmental stresses on the estuarine system (which are already moderately high) with
the expection of N inputs and further TSC. Our concern is about a future scenario where QV
increases within the range around 10-25%, together with projected temperature increases and
economic growth, for which significant impacts are expected in the estuarine and coastal systems.
Considering the fact that seasonal temperature, precipitation and streamflow cycles are not
superposed, any changes should modify seasonal circulation and mixing state or stability (vertical
difference in salinity as a function of depth: dS/dZ), inducing further environmental shifts and
changes (i.e. Δ gas and nutrient exchanges, ∆ P-R, increase in HABs occurrence, with a probable
increase in both the degree and occurrence of hypoxic events, as well as an increase in the
vulnerability of fishermen and low-lying areas.
Capacity building outcomes and remaining needs
Capacity building
LA 32 team members have developed Earth System Science and Global Change lectures for a
course devoted to High School teachers of Earth and Space Sciences.
LA 32 team members attended to about ten workshops and courses devoted to climate scenarios,
climate modeling, vulnerablity and adaptation assessment methods, GIS and Environmental
Monitoring, Estuarine Systems, Remote Sensing, Global Enviromental Change and Participatroy
Processes..
GJ Nagy, A Ponce and G Sención attended to the AIACC Workshop on Vulnerability and
Adaptation in Trieste, Italy (2002).
LA 32 team members developed lectures on Global Change for a Graduate International course
(UdelaR-AEO-Scripps) on Ocean Color for Latin American students.
LA 32 team members updated the course on Earth System Science and Global Environmental
Change for the Master of Science in Env. Sciences, Facultad de Ciencias, UdelaR.
LA 32 team members were invited by DINAMA (Uruguay) to present their results on June 2005.
xvi
Remaining needs
1. To improve our capacities in:
•
Vulnerability mapping
•
Integrated climatic, environmental and socioeconomic analysis.
•
Quantitative multicriteria assessments of stakeholders perception
•
Particpatory proceesses and stakeholders engagement
2. To develop an update socioeconomic national scenario including all sectors involved in our
research. We assume that this task will be conducted during the the 3rd National Communication
(TNC).
National communications, science-policy linkages and stakeholder
engagement
LA-32 team members participated / were engaged or will participate in:
•
the revision of the 2nd National Communication SNC) Draft under the UNFCC.
•
in several workshops (2003-2005) organized by the Ministry of the Environment: Synergies
of the three conventions: Biodiversity, Climate Change and Desertification.
•
G J Nagy was nomitated by the IPCC to act as a Lead Author of Chapter 13 (Working
Group II, Latin America – coasts). He was supported by the Directorate of the Environment
of the Uruguayan Ministry of Foreign Affairs, the Unit of Climate Change of the
Uruguayan Ministry of the Environment and AIACC.
•
a series of 4 Prospective workshops organized by the Minisitry of the Environment:
“Reflections on Uruguay 2025” (Coastal Zone Working Group).
•
a LA-26 stakeholders meeting in Buenos Aires (July, 2004).
•
the draft draft on coastal systems vulnerability and adaptation (Unit of Climate Change of
the Ministry of the Environment in order to plan the Third National Communication.
•
LA-32 team members were engaged by the UCC-ME to update climate and environmental
time-series for the main watersheds and coastal zone of Uruguay and develop high
resolution climate models (PRECIS). This information will serve to write the 3rd National
Communication (TNC) under the UNFCC.
•
a meeting with the GEF consultant (Pascal Girot) whos evaluated the capacity to undertake
vulnerability and adaptation assessments and climate modeling for the coastal systems,
fresh and estuarine waters during the TNC.
Policy implications and future directions
LA-32 team members participated / were engaged or will participate in:
•
the development of cooperation with the Directorates for Water Resources (Min. Of Public
Works) and Hydrography and Oceanography (Min.of Defence), the Public system of
education (elementary, high and technical schools) and an agreement with the Russian
Academy of Sciences Institute of Oceanology.
•
the Peruvian Report on Vulnerability to Climate Change CONAMA-Perú, 2005).
•
a pre- and full proposal on Global Change and Sustainable Livelihood in the Rio de la Plata Basin
(IAI-CRN II call). If approved, this project will be the core of future development of global
change and sustainability research during the period 2006 – 2010.
xvii
•
a presentation on current and future climatic and environmental scenarios for the Uruguay
river basin and stream (Bi-national Uruguay river Management Committee: Argentina Uruguay). If future cooperation is agreed, vulnerability assessments and adaptation
policies to cope with global envrionmental changes should be planned.
•
a presentation on current and future climatic and environmental scenarios and impacts for
the Rio de la Plata Basin and Estuary to ONGs, journalists and congressmen.
xviii
1 Introduction
1.1
Problem
The Third Assessment Report (TAR) of the IPCC (2001), referred to as TAR, identified two main
environmental problems in South America: Land Use Changes and ENSO variability. The Rio de la
Plata basin (RPB) and estuary (RP) have been substantially influenced by human activities in recent
decades and are highly sensitive to climate extremes and changing precipitation patterns. The
weight of scientific evidence suggests that there is now a discernible human influence on
environmental deterioration within the RPB (3,2 x 1011 km2) and RP (3.6 x 104 km2) in addition to a
change of precipitation patterns with the consequent increase in river flow (QV) and decrease in
salinity.
The Paraná-Uruguay system river water discharge increased by ~30% since 1961 (Nagy et al. 1997,
2002). The region is highly sensitive to climate extremes such as ENSO, and also suffers from
increasing land cover change and misuse of land, which in turn have changed the infiltration:
runoff ratio. On the other hand, both the population increase (> 1% y-1) and fertilizer application (>
20 kg ha-1) have led to an increase in N and P input to the coastal waters.
Population of the RPB increased by 90% from 1961 to 1994 (Baethgen et al., 2001) leading to an
increase in pressures on watersheds. For instance they are heavily utilized for agriculture,
damming, fertilizer application, and there is a heavy discharge of wastewater from point sources
(wastewater treatment from domestic input is ~ 20%), and of nutrients from non-point sources.
(Pizarro and Orlando, 1985; Tucci and Clarke, 1998; Nagy, 2000; Nagy et al., 2002a).
The Uruguay River Basin (URB) has an area of 297,000 km2 in Brazil, Argentina and Uruguay and a
population density of 25 /km2. Some relevant land-use data are: 4% of wetlands, 2% of protected
areas, 44% of cropland and 45% of grassland areas. Main enviromental deteriortation data are: 20%
of eroded area, 92% lost of original forest, a rate of 12% of deforestation. There are two large dams
on the River Uruguay (WRI, 1998).
Coastal waters provide habitat for some of the most productive ecosystems on earth. These
resources are in danger from excess input of nutrients (NCR 2000). Nearly all estuarine waters now
exhibit some symptoms of eutrophication, although the level of nutrient inputs required to produce
the symptoms is variable (sensitivity). As a result of the changing climatic and nonclimate
conditions over the past fifty years both the natural susceptibility (vulnerability) to flush and dilute
nutrients and eutrophication (impact) increased. The RP is susceptible and eutrophic. Within the
frontal zone such processes like nutrient removal, in situ production of organic matter (CH20), and
denitrification are estimated to be high (Nagy, 2000). The main symptoms of eutrophication are an
increase of organic matter ”expressed” as increased algal biomass and production, oxygen stress,
and Harmful Algal Blooms (HABs).
The increase in QV variability vary both the location and structure of the Estuarine Front-EF,
affecting the sites of reproduction and catch of fishes. Coastal fisheries are impacted because of the
changing accessibility of the fishing area (i.e. 1987-1988 and 1997-1999) as shown in Figure 2. The
Canal Oriental behaves as a conduit channel of QU that should control stratification, phytoplankton
blooms and high levels of in situ CH20 production, which in turn is oxidized below the halocline.
Stratification induce the development of hypoxic conditions, leading to a heterotrophic state
(destruction of CH20 and source of CO2). The pronounced reduction of QV during La Niña, i.e. in
November 1999, and the consequent increase in flushing time (ft), led to eutrophic symptoms
(Nagy et al., 2001a).
1
ROU
Kiyú
P. Blancas
a
c
b
San Luis
d
a
RA
Fig. 2: Estuarine Front location under different ENSO conditions: a) Strong La Niña event (1999-2000), b) Typical
c) Moderate El Niño (winter 1987) d) strong El Niño 1997-1998 / 2002 – 2003; c + d: estuarine plume (modified
from Nagy et al., 2002b).
1.2
Primary Objectives and Expected Outputs of the Project by
2001 updated To 2004
Overall goal of the project was: i) to assess vulnerability and impacts of/on the estuarine waters,
coast and resources of the RP and ii) to plan adaptation strategies for coastal fisheries (Adaptive
Control Information System-ACIS) in order to cope with climate change and nonclimate scenarios.
The key questions to be addressed were:
•
How sensitive is the system to Climate Variability and Change?
•
Is eutrophication related to Climate Change and Variability?
•
Is the coastal fishery system sustainable under increased river flow variability?
•
Will the coastal zone be heavily impacted over the next few decades?
The secondary questions to be answered were:
•
How would an increase of QV and NI affect eutrophication (i.e. oxygen stress and HABs) of
the estuarine subsystems?
•
Is the frontal zone role as a site for reproduction, nursery and feeding of fisheries resources
modified by short- and long-term hydroclimatic variability?
•
How does the consecutive occurrence of hydroclimatic extremes, i.e. 1998-2000 period,
affect the adaptive capacity of the estuarine ecosystems?
1.3
The Main Expected Outputs of the Project
These were:
1. To improve the analysis of current climatic and nonclimate baselines.
2
2. To develop reference projections of a range of hydroclimatic and nonclimate factors which are
anticipated to change in order to obtain credible estimates of future impacts in salinity,
eutrophication, trophic status, fisheries resources and ecosystem services.
3. To obtain economic values of the impacts affecting direct use activities and indirect uses,
according to the projected scenarios.
4. To study a set of short-term processes, i.e. oxygen stress, to explain the possible response of the
ecosystem to hydroclimatic and non-climatic changing scenarios.
5. To improve the systems and methods for long-term monitoring and understanding the
consequences of climate change and other stresses on the environmental systems.
6. To foster science capacity building to undertake the assessment of vulnerability and adaptation
to climate and nonclimate change.
7. To plan an Adaptive Control Information System (ACIS) for implementing anticipatory
measures, to offset adverse effects of changing scenarios.
1.4
The Exposed Analyzed Units
These were:
i) the estuarine frontal zone (Figure 2) and ii) the Santa Lucía river lower basin, estuary and
associated coastal zone. We focused on the understanding of ecosystem response in order to obtain
credible estimates of future vulnerability and impacts on:
•
trophic state changes (increase in symptoms of eutrophication),
•
coastal fisheries and associated livelihood vulnerability, and
•
water resources, TS and SLR in the Santa Lucia river lower basin, estuary and coastal
zone.
Time horizons considered were from the past 30 years and present through 2050 / 2080.
3
2 Characterization of Current Climate and Scenarios of
Future Climate Change
2.1
Activities Conducted on Current Climate Baselines
We have engaged or worked with scientists from national institutions devoted to climatic and
environmental monitoring. We gathered and bought data, updated several climate and non-climate
trends and built capacity to pursuit data analysis. Most relevant baselines and trends (temperature,
precipitation, sea level pressure, river flows, sea level rise, salinity), were almost completed beyond
the initial goal of the project.
2.2
Scientific Methods and Data
The overall approach taken in this multisectoral research has consisted of combining several
approaches and methods. We can divide them into three main ones: 1. Emiprical / Statistical; 2Global Circulation Models (GCM) and 3- Downscaling techiniques.
2.2.1 Empirical / statiscal
We gathered, reanalyzed and reconstructed climatic, hydrological and oceanographic time-series
from available data and / or proxy variables when needed to fill gaps. Regression models and
cross-correlation between time-series were the main statistical method.
2.2.2 GCMs
We used all the IPCC GCMs and compared their results to current baselines of sea level pressure,
temperature and precipitations (1961-1900). We selected seven available runs from IPCC
Distribution Data Center, using socioeconomic SRES-A2 and B2 forcing scenario. We have
compared sea level pressure, surface air temperature and precipitation from the models, against
observed climate fields, trying to estimate regional performance of the control simulations (1961 –
1990 baseline climate scenarios). The comparison between the monthly and annual SLP fields
shows that only four models (HADCM3, CSIRO-mk2, ECHAM4, GFDL-R30) have an acceptable
agreement with the observed SLP field and are able to represent the position and intensity of the
pressure systems and the annual cycle. In all cases, precipitation is underestimated within the Río
de la Plata basin. The comparison between the monthly and annual temperature fields shows that
in general all the models have an acceptable agreement with the observed fields.
The future climate change scenarios, for precipitation and temperature, over Southern cone of
South America were constructed for 2020, 2050 and 2080s.
2.2.3 Statistical and dynamical downscaling experiments.
In order to generate precipitation and temperature daily time series based on future climate change
scenarios from the GCMs we selected the both statistical and dynamical techniques for downscaling
to bridge the spatial and temporal resolution gaps between climate models and vulnerability
assessments requirements. We made use of statistical downscaling technique trough the SDSM
model (Wilby et al., 2001). The selected predictor variables (taken from NCEP reanalysis) for daily
precipitation are SLP, zonal and meridian wind components at 850 hPa. We selected four locations
within the RdlP basin during the period 1996 – 2001: Buenos Aires, Santa Fe, Montevideo and Salto.
SDSM model showed to be a valuable tool to represent some of the characteristics that existed in
the regional precipitation data.
4
Another tool used to generate future high resolution scenarios over Southeastern South America
was PRECIS (Hadley Center’s regional climate modeling system). These scenarios are being
developed and we do not have results yet.
2.2.4 Overall framework and Methods
Overall framework for vulnerability and adaptation research was the Framework for second
generation assessment” (SEI, 2001).
•
a multi-level indicator of vulnerability to climate change (adapted from Moss, 1999) as
presented in Figure 3.
•
a driver–Pressure-State-Impact-Response (d-PSIR) framework (as shown in trophic state;
section 3.3).
•
vulnerability indicators, index and matrices, regression models, fishing activity. A
combination of objective values and expert judgment was used in order to assess social,
economic, environmental and legal indicators of sensitivity of the fishermen’s community
as well as to assess HABs impact. Non-climate projections, SRES A2 / B2 climatic scenarios
and GCMs. Each indicator was classified as low, moderate and high and was given values
1, 2 and 3 respectively.
•
causal loop diagrams (Ford, 1999) for water resources, ecosystem, coastal fisheries and
settlement (as shown in coastal fishery sytem; section 5.2).
CLIMATE
& NON
- CLIMATE FACTORS
Vulnerability index
Water
Ecosystem
Coastal Zone
Coping
Water
quality
Accessibility to
Fishing areas
Settlements
Health
Capacity Indicators
% protected lands
Weather
forecasting
Outreach/
awareness
Indicators of sensitivity/exposure
River flow
Frontal zone location
Fq Storm surges
% Fishing days
% Pop at risk
Pressure State Impact Response Matrix
Future
Scenarios
Adaptation
Framework
Capacity
Building
ACIS
Monitoring
Early Warning
Response System
Fig. 3: Multi-level indicator of Vulnerability to Climate Variability and Change for coastal systems of the Rio de la
Plata (modified from Ponce et al., 2002, adapted from Moss et al., 1999).
•
Guidance for Vulnerability and Adaptation Assessment (US Country Studies Program,
1994).
•
Guidelines on the Use of Scenario Data for Climate Impact and Adaptation Assessments
(Carter et al.1999), TAR Working Group II), IPCC data and models (DDC) vii) adapting to
Climate Change: Assessments and Issues (Smith et al. 1996).
5
•
United Kingdom Climate Impact Programme Technical Report. Climate adaptation: Risk,
Uncertainty and Decision-Making (UKCIP, 2000).
•
an empirical-statistical approach to investigate ecosystem impacts, responses and adaptive
capacity, and vulnerability to climatic variability and extremes, and to non-climate
pressures based on Observations, Data, Current Baselines and Incremental scenarios of
appropriated climate and non-climate variables.
2.3
Selected Climate Models
Selected socioeconomic scenarios, time horizons and GCM were A2 and B2, 2020 / 2050 / 2080,
HADCM3 and ECHAM4/OPYC3 respectively. There is a lack of appropiate spatial resolution
suggesting the need of improving downscaling techniques to validate scenarios for the spatial scale
of Uruguay. Lack of daily outputs from both selected models precludes to perform statistical
downscaling with SDSM model for future climate scenarios.
2.4
Indicators and Proxy Variables
Vulnerability = V; Impact = I; Adaptive Capacity = AC
2.4.1 Environment (weather/water quality/ecosystem/coastal zone)
N-S: (nutrient sources - nutrient sinks)
V: Stratif ication index; Stratif ication-Circulation Parameter (S-C)
V: Residence Time; Flushing Time; 1/dilution Vs Flush ing ; River Flow / upper layer volume
V-I: Multivariable Enrichment state Index; TRIX state index
V: NOAA (nutrient) export potentia l
V-I: Nb of reported and verified organisms outbreaks (HABs) over the last five years.
V-I: ENSO indices (severa l ones); multivariable index.
V: Nb of days (past 5 years) during which the Mx wind speed > th an 20% h igher th an the
average for th at month
V: Nb of 5-days precipita tion events > th an 20% h igh er th an the average for th at year.
V: Nb of storm surges with run up greater th an 2 m above mean seal level at Montevideo.
V-I: Fertil izer consumption / surface unit
V-AC: Irrigated surface / population
V: Coasta l Vulnerability Index (tide range, wave height, shoreline erosion, SLR, slope)
V-I: HydroClimatic Index (temp., precipita tion, river flow, SL pressure and gradients, SLR)
V-AC: % Land managed
V: Population at flood risk from sea level rise and storm surges
V: % of land area less than 5 m above sea level.
2.4.2 Coastal Fishery System
(water resources/ecosystem/fishery/settlements)
V-AC: % of income from fishing
V-I: ENSO indices (several ones); multivariable index.
V: Stormy days (% winds > 8 ms-1); fishing days;
V-I-AC: Fishing days (F) / stormy days (F /S)
V-AC:Nb and weight of fishing boats activity / month
V-I: Fish catch (CB: biomass and CI income)
AC-I: D F/CB and/or F/CI (increase: Adaptive capacity; decrease: Impact)
V-AC: Human Development Index (national and community level)
V-AC: GDP (national /regional/community level), Gini Index
6
V-AC: Literacy (%); % of female literacy.
V-AC:% of total income from fishery activity
V-I: Number of industrial fishing boats
V: Population at flood risk from sea level rise and storm surges: Impact)
V-AC: Human Development Index (national and community level)
V-AC: GDP (national /regional/co
V-I: % of fisheries stocks over-fished
V-AC: Number of expanded fisheries efforts over the last five years (within the frontal zone)
Several of these indicators have not been used yet, whereas other were recently adopted and are
explained in the text.
2.5 Results of Long-Term Climatic, Hydrologic and
Oceanographic Trends
We have updated climatic, hydrologic and oceanographic yearly long-term trends up to present
(temperature, precipitation, sea level pressure, river flows, sea level rise, salinity)1.
2.5.1 Temperature.
Air temperature at Montevideo has increased ~0.8 C during the period 1883 – 2003 (Bidegain et al.,
2005) as presented in Figure 4, mostly during the last three decades, when the increase reached
about 0.9 C with a maximorum of 17.8º C in 2001(Figure 4).
YEARLY MEAN TEMPERATURE (°C)
MONTEVIDEO 1883-2003
18,0
TEMPERATURE (°C)
17,5
17,0
16,5
16,0
15,5
15,0
14,5
14,0
1883 1890
1897 1904 1911
1918 1925 1932
1939 1946 1953 1960
1967 1974 1981
Fig. 4: Evolution of yearly air temperature at El Prado, Montevideo (1883 – 2003). From
1988 1995
Bidegain et al., (2005).
2.5.2 Precipitation
Precipitations have increased during the last three to four decades all over the RP basin and
Uruguay by ≥ 20% (Kane et al., 2002; Berbery and Barros, 2002; Blixen et al., submitted). In Figure 6
we show the time-series of yearly precipitation at Montevideo (1883-2003). Both the trend line and
the minima have significant increased, as well, in a less degree, the maxima. This increase is
1
This section is based upon a technical report to the Ministry of the Environment (AIACC LA-32).
7
inequally distributed all along the year, being maximum during October and November. These
patterns are very similar for other stations in Southern Uruguay (Bidegain et al., 2005).
Evolution of Air Temperature at El Prado, Montevideo (1974 - 2003)
Temperature has increased by 1.1 - 1.2 ºC since 1900.
18
17.8
y = 0,0307x + 16,414
R 2 = 0,4074
17.6
17.4
Increase = 0.9 ºC
17.2
17
16.8
16.6
16.4
16.2
16
1
2
3
4
5
6
7
8
9
10
11
12
13
16
17
Years 1974
14
15
-
18
19
20
21
22
23
24
25
26
27
28
29
30
2003
Fig. 5: Evolution of yearly air temperature at Montevideo (1974-2003). From Nagy et al, (2004).
Fig. 6: Evolution of yearly precipitations at El Prado, Montevideo (1883 – 2003). From
Bidegain et al., (2005)
2.5.3 River flows
Flows of Rivers Paraná and Uruguay have increased by at least 35% during the last four to five
decades (Figures 7, 8) approximateley one fourth to one third more than the increase in
precipitations. Part of these trends and most fluctuations are associated with ENSO events, which is
shown for the period 2000-2002 (Figure 9).
8
Fig. 7: River Uruguay flow at Salto from 1921 to 2003. From Bidegain et al., (2005).
35000
30000
25000
20000
15000
10000
5000
0
1930
1940
1950
1960
1970
1980
1990
2000
Years
Fig. 8: River Paraná flow from 1940 to 2000. From Nagy et al., (2002c).
Fig. 9: Relationship between monthly SST 3.4 and river flows of Rivers Uruguay (black) and Paraná (red) from
January 2000 to December 2002. Horizontal lines indicate strong La Niña (bottom), neutral and Strong El Niño
(upper). A better relationship is found for River Uruguay, especially in 2002 (modified from Severov et al., 2004
and Nagy et al., submitted).
2.5.4 Sea level pressure.
Sea Level Pressure (SLP) at Montevideo decreased by 1.3 hPa during the period 1901 – 2001, which
is assñociated to the southward displacemente of the subtropical high pressure belt (Bidegain et al.,
2005) as presented in Figure 10.
9
Sea Level Atmospheric Pressure (hPa) at El Prado-Montevideo (1901 - 2001)
1019
1018
1017
1016
1015
1014
1013
1901
1906
1911
1916
1921
1926
1931
1936
1941
1946
1951
1956
1961
1966
1971
1976
1981
1986
1991
1996
2001
Fig. 10: Evolution of Sea Level Pressure at El Prado, Montevideo (1901 – 2001).
2.5.5 Sea level rise
Sea Level Rise (SLR) has increased by 11 cm during the period 1901 – 2003 (Nagy et al., 2005) as
presented in Figure 11.
RELATIVE MEAN SEA LEVEL RISE -AT MONTEVIDEO (1902-2000)
115
110
y = 0.0928x - 86.16
2
R = 0.2307
(cm)
105
100
95
90
85
80
1902 1908 1914 1920 1926 1932 1938 1944 1950 1956 1962 1968 1974 1980 1986 1992 1998
YEARS
Fig. 11: Sea Level Rise at Montevideo for the period 1902 – 2000 (Pshennikov et al., 2003).
2.5.6 Salinity
Salinity has decreased by ~3 during the period 1906 – 2000 (Bidegain et al., 2005) as presented in
Figure 12. Time-series is discontinuous but allows to depict that at the beginning of the past century
salinities were 10-12 and that during the last five decades have decreased to ~8, in agreement with
the increase and fluctuations of river flows (i.e. maximum salinity during the drought period 1942 1947). The value reported for 1919 is the centered mean of the period 1917-1926 calculated from
monthly means because yearly data are not available.
10
Fig. 12: Evolution of yearly mean salinity at Montevideo (discotinuous time-series 1906-2000).
2.6
Socio-Economic Futures
We modified the scenarios developed by the Unit of Climate Change-UCC (Ministry of the
Environment) for 2000 and 2050 (Table 1) and socioeconomic SRES-A2 and B2 forcing scenarios for
regional climate modeling. These scenarios are an approach to the future availability of resources to
cope with eventual climatic changes (UKCIP, 2000). SRES-A1 assumes global economic
convergence, better income distribution, technological changes, high environmental pressures, and
annual rates of WGP and NGP of 3.7 % and ≥ 4.0 % respectively, whereas SRES-B2 assumes low
economic growth (1%) and an increase in environmental concern. For the latter, an index was
developed which takes into account the ratio environmental investments / NGP. Increases in
economic and dependency proxy variables suggests a better and worst adaptive capacity
respectively, whereas enviromental variables are useful to estimate pressures over the vulnerability
and adaptive capacity of the environment. We have also developed scenarios for coastal fisheries
activity (see adaptation).
Sc. A1 - Variables
Population
NGP
NGP/capita
Land use
Non-agricultural
Agriculture / Cattle
Agriculture
Cattle breeding
Forestation
Others
Water Resources
Offer
Production
Withdrawal
Urbanization
GINI Index
Units
106 persons
U$S year 2000
U$S year 2000
103 Ha
106 m3
%
%
Year 2000
3.337
20.042
6.006
Year 2050
4.262
142.432
33.419
Var % total
27.72%
610,67
456,67
% annual
0.49
4,00
3,49
1.168
16.334
985
14.431
639
279
1.168
16.334
950
13.250
2.000
134
0
0
-3.55
-8.18
212.98
0
0
-0.07
-0.17
2.31
4.200
380
200
0.91
0.50
4.200
690
421
0.95
0.45
0
81.6
110.5
4.39
-0.1
0
1.20
1.50
0.086
-0.21
11
Sc. B2 - Variables
Units
Population
106 persons
NGP
U$S year 2000
NGP/capita
U$S year 2000
Land use
103 Ha
Non-agricultural
Agriculture / Cattle
Agriculture
Cattle breeding
Forestation
Others
Water Resources
106 m3
Offer
Production
Withdrawal
Urbanization
%
GINI Index
%
Environmental Index EI / NGP (%)
Year 2000
3.337
20.042
6.006
Year 2050
4.262
32.292
33.419
Var % total
27.72%
64,46
456,67
% annual
0.49
1,00
0,51
1.168
16.334
985
14,431
639
279
1.168
16.334
950
14,150
1,100
134
0
0
-3.55
-8.18
212.98
0
0
-0.07
-0.04
1,09
-1,46
4.200
380
200
0.91
0.50
0,05
4.200
512
291
0.95
0.50
0,1
0
81.6
110.5
4.39
0.1
100,0
0
1.20
1.50
0.086
0
Table 1: Current (2000) and future (2050) national socioeconomic scenarios (SRES A-1, top) and B-2 (below)
(modified from data from the UCC; Sención, 2002; Nagy et al., 2002-).
12
3 Impacts and Vulnerability
The aim of this section is to describe the exposed systems, sub-systems and sectors. First of all, we
focus on the physical and biogeochemical processes in order to understand the vulnerability,
impacts and adaptive capacity of /on estuarine waters, ecosystem state and coastal fisheries
resources. Secondly, we present the assessment of vulnerability and adaptive capacity, including
the pilot coastal zone study site (Western Montevideo).
3.1
Description of the Studied System and Vulnerable Sectors
3.1.1 Location and geomorphology of the Rio de la Plata river estuary
The Rio de la Plata (34º00’-36º10’ S and 55º00’W) covers an area of 38 x 103 km2, draining the second
largest river basin of Latin America (3,1 x 106 km2; Figure 13). From a geomorphologic point of view it
can be defined as “a funnel-shaped coastal plain tidal river with a semienclosed shelf area at the mouth
and a river palaeovalley at the northern coast that favours river discharge and sediment transport to
the adjacent shelf (López Laborde and Nagy 1999).
3.1.2 Meteorology, climatology, hydrology and hydrography
The general atmospheric circulation is controlled by the influence of the quasi-permanent South
Atlantic high pressure system and the continuous passage of low pressure systems. This general
circulation is modified by semi-permanent low pressure system located over Chaco (Paraguay)
generating prevailing NE to SE winds.
Rio de la Plata’s usual weather is controlled by several factors. One of them is the passage of polar
air masses. They penetrate into the continent from the patagonian region with a NE direction.
When air masses cross over the Rio de la Plata, wind direction changes from North to South, often
generating strong wind gusts and rainy events. When the air masses reach Brazil their movement is
reduced and the air is warmed. Later, warm airmasses return to the South originating norhterly
winds, which carry new maritime or continental tropical warm and moist air masses. Northern
winds stop when a new polar air mass begins to advance from the Patagonian region to the North.
The most frequent storms affecting the Rio de la Plata are called ”Sudestadas” (Southeasterlies
winds). They are produced when both a frontal system (with SW-NE trajectoires) is located over the
mouth of the RP and a low presure system is located along the Uruguayan Atlantic coast,
generating strong SE-winds. Usually the storms affect the area for several days. The coastal area is
also affected by southwesterlies winds (“Pampero”). They originate from the passage of polar air
masses arriving from the south of the Andean Mountain Range. The Pampero is a strong (13-25 m s1
), dry and cold wind (López Laborde and Nagy 1999).
The estimated freshwater inflow (QV) to the system is fed by the Paraná river branches (Paraná
Guazú ∼58%, Paraná Las Palmas ∼17%) and River Uruguay (25%). This inflow trifurcates due to the
presence of banks and tidal channels (López Laborde and Nagy, 1999). It is directed into three flow
corridors (northern, middle and southern ones), corresponding to the flows of rivers Uruguay,
Paraná Las Palmas and Paraná Guazú respectively (Figures 4 and 6), where advection
predominates over turbulence and lateral mixing (Menéndez, 2001).
A hydroclimatic shift occurred in the Río de la Plata basin in the early seventies (García and Vargas,
1998), and runoff fluctuations and trends have increased partly associated with ENSO related
variability (Nagy et al, 1997). Seasonal and interannual total freshwater discharge (QV) typically
varies between 22000 and 28000 m3 s-1 on both seasonal and interannual time-scales (mean QV
∼26,000 m3 s-1 for the nineties), with extreme values during El Niño (more than 30,000 m3 s-1) and La
Niña (less than 20,000 m3 s-1) (Nagy et al. 2000b). The major monthly variability of salinity off
Montevideo (1998-2000) is explained by QU which in turn has high correlation with ENSO
variability (Nagy et al., 2002b). This flow is estimated to be the main contribution to the northern
corridor (Uruguayan coast) from ~April to ~October (Nagy et al., submitted).
13
Climatologically, the Río de la Plata has maximum discharge in March-April, associated with the
River Paraná flood; in June, associated with both rivers discharge, and in September-October,
associated with a secondary flood of the River Uruguay. The minimum discharge usually occurs
around January. During recent El Niño years, the flow of River Uruguay tended to increase in April
as well. Extremes three to four times greater than the average are often associated with El Niño.
Therefore, winds and river discharge have similar temporal patterns in relation to their effect on
salinity fields distribution and turbidity front location, with onshore winds and low discharge
during Summer, and offshore winds and high discharge in Fall-Winter (Framiñán & Brown, 1996;
Guerrero et al., 1997; Nagy et al., 1997). Simionato et al. (2002) used river discharges of 20,000 and
30,000 m3 s-1 as low and high discharge forcings (Nagy et al., 1997) to perform 3-D baroclinic
experiments. They concluded that: The winter conditions is mainly explained by a combination
between the river discharge and the Coriolis effect, which deflects the fresh water plume to the N
along the coast. During the summer, even if the amount of river discharge is large enough to
produce a similar picture to the one observed in winter, the predominant easterly wind inhibit the
plume extension and force the fresh water to the W along the Uruguayan coast, and SW on the
Argentinean side. Finally, Escobar et al. (2004) suggests that the subtropical Atlantic anticyclone has
tended to move towards the south in recent decades, contributing to an increase in the easterly
wind over Rio de la Plata and subjacent sea.
According to the terminology of the stratification-circulation (S-C) pattern classification of Hansen
& Rattray (1966) the Río de la Plata is a ”Type 2b” system (the flow reverse with depth,
corresponding to the partially mixed estuary with appreciable stratification; López Laborde and
Nagy 1999). This pattern varies with river flow, wind and tidal height/depth ratio from 1b (net
flow is seaward at all depths) to 4 (salt wedge highly stratified). The latter is often found in the
Canal Oriental where stratification lasts over successive tidal cycles (López Laborde et al., 1996; Nagy
et al. 2002b).
The average (for the 1990s) residence time of water within the estuary was estimated to be 35 and
40 days for the surface layer and bottom layers, respectively (QV= 26,000 m3 s-1; end member
salinities = 0.3 and 29; surface and bottom salinities= 15 and 27 psu, respectively) (Nagy 2000; Nagy
et al. 2002b).
Fig. 13: Rio de la Plata location and cited regions.
3.1.3 Estuarine waters dynamics, ecosystem and services
Research on the estuarine waters of the Rio de la Plata was concentrated on four subjects,
14
•
Estuarine Front Dynamics.
•
Water Column Structure and associated biogeochemical processes.
•
Coastal Fishery System.
•
Trophic State Changes and Symptoms of Eutrophication.
all of which are interrelated and strongly dependent on hydroclimatic variability (∆ QV).
By definition estuaries are mixing zones between rivers and the sea. The inputs from both ends and
the gradients established are quintessential features of estuarine ecosystems. Changes in the
delivery of fresh water may, therefore, produce among the most important responses of estuarine
ecosystems to future climate variability and change (Boesch, 2002).
A coupled model diagram of the feedbacks affecting the hydrologic cycle and coastal ecosystems of
the RdlP is shown in Figure 14.
Fig. 14: Coupled model diagram of the processes and feedbacks affecting the hydrologic cycle and coastal ecosystems
of the Rio de la Plata Basin and coastal ecosystems (from Berbery et al., 2003).
3.1.4 Estuarine front (EF)
Estuarine frontal dynamics (location, displacement and structure) was studied on weekly, monthly
and yearly timescales as a function of river flow fluctuations (climatic timescale: seasonal and
ENSO-driven fluctuations) and synoptic timescale (weather development <10 days). The EF, a
physical feature related to the salt intrusion limit (Figure 15), is the main physical and ecological
subsystem of the RP. It is the site for reproductive cycles and early stages of life of several
commercial estuarine species, as well as of a high assimilation of primary nutrients and primary
production of organic matter (P) in the upper water column, degradation of organic matter (R),
oxygen consumption and denitrification in the bottom water column (Nagy 2000; Nagy et al 2002c;
Norbis et al., 2004; Lappo et al., 2005).
15
Fig. 15: Estuarine Front (EF) of the Rio de la Plata (SeaWIFS image)
Thus, ecological goods and services such as coastal fisheries and primary production show peaks
within the EF and depend on it’s dynamics, which is ultimately controlled by climatic forcings in
the RP basin.
This research was conducted together with Udelar funded project CSIC-Frontal Variability of the Rio
de la Plata (PI: Professor DN Severov, Investigators: Valentina Pshennikov, Juan J Lagomarsino and
student Maite de los Santos) and the Joint Program between the Russian Academy of Sciences
(RAS) and the Facultad de Ciencias-UdelaR (with the participation of Dr. Evgeni Morozov, RAS).
Up to four distinct fronts are distinguished: Main Turbidity Front (MTF), Main Marine Front
(MMF), Secondary Turbidity Front (STF) and Secondary Marine Front (SMF) between riverine,
estuarine and marine waters (Figure 16). Their number, location and shape are related to the
volume and timining of freshwater discharge of each tributary. For instance, along the Uruguayan
coast most of the variability in salinity and turbidity fields are associated with the flow of River
Uruguay. Over the studied period the influence of both La Niña (beginning of 2000) and El Niño
(April 2002 – beginning of 2003) was observed superimposed to seasonal variability.
Both long-term river flow series of freshwater discharge and future climate scenarios for
Southeastern Southamerica suggest that a drammatic change in the location of fronts is occurring
since 1970 and could continue over the next few decades (Severov et al., 2004; Nagy et al., submitted).
Sequential weekly downloading of SeaWIFS images, visual observation from the coast and
oceanographic cruises along the Canal Oriental allowed to study the location, vertical structure and
displacement of fronts from January 2000 to December 2004. A sketch of the location of the fronts of
the RdlP was drawn (see Figure 16) after Severov et al. (2003, 2004), data taken from the RAS
Research Vessel Akademik Sergei Vavilov on November 2003 (Lappo et al., 2005) and a SeaWIFS image
(November 27, 2003).
A synthesis of the main results about the EF dynamics and the different fronts presented in Figure
16 is presented in table 2.
16
Fig. 16: Sketch of the river flow corridors and front-lines of the Rio de la Plata. Distance down-river from Colonia is
shown in Km.. The estuarine front includes the MTF and SMF (Nagy et al., submitted to JASR).
a- Average Location
b- Extreme Locations
Front
MTF
SMF
MMF
Mean (km)
St. deviation
Maximum
Minimum
Salinity
Nitrates
Chlorophyll
139
49
280
15
1-3
10-20
1-3
183
56
360
20
10-12
3-6
3-20
292
66
375
135
20-22
1-3
2-5
Month
QV
/ year
(m3/s)
03 / 00
01 / 01
01 / 02
07 / 00
10 / 02
04 / 02
05 / 03
15
22
16
22
20
24
27
QU
(%)
10
23
15
29
35
18
30
MTF SMF
15
20
30
265
180
250
270
20
50
140
360
270
320
380
MMF
135
375
170
375
350
380
320
Table 2: a- Average fronts loci down-river from Colonia (DRC), ranges of salinity, nitrates (uM) and chl-a
(ug/l), and 3-months running mean of extreme QV (103 m3/s),% QU, and b- extreme fronts loci (MTF,
SMF, MMF) (from Nagy et al., submitted to JASR).
3.1.4.1.
Water column structure and associated biogeochemical processes
We aim to briefly describe the state of the art of water column structure and the processes that
cause variability in coastal waters over timescales of hours, days, weeks and longer in the RP,
including some results obtained by AIACC LA-32.
Variations in a number of water column physical, chemical and biological properties can be driven
by either internal processes such as biological activity and chemical reactions (i.e. P and R of
organic matter-CH20), and mixing of waters, or by external forcing from the atmosphere, from
runoff and inputs from land, or from exchanges with offshore waters of energy, mass, and biota.
Of primary interest are salinity, temperature, dissolved oxygen and chlorophyll because their
variations encompass a wide range of processes such as: i) in situ photosynthesis, ii) air-sea gas
exchange (02, C02, N2 and N20), iii) response to meteorological conditions (solar radiation, wind
velocity, heat exchange), iv) physical processes such as tidal mixing and stratification (bottom
salinity – surface salinity: ΔS), v) runoff from land, and vi) anthropogenic inputs (N, P and organic
matter- CH20).
17
We selected six oceanographic cruises since the early 80’ which were conducted under different
physical forcings within the typical range of river flow (QV: 20-32 x 103m3s-1) and wind velocity < 8
m/s (not able to mix the deep water column with a depth > 10 m). Cruises are ordered according to
the increasing persistence of stratification conditions (Table 3) from mixing by strong winds (A) to
two weeks (B) and five weeks of vertical stability with calm weather (C), high river flow (D-E), and
(F) long-term average.
Oceanographic Cruises
Variables
QV (103m3s-1)
Mixing Index *
A0U (µM)**
N0X (µM)***
DIN (µM)****
DIP (µM)*****
N/P
A
25
0.02
18
0.4
3.2
0.5
∼6
B
24
0.39
152
3.0
6.6
1.1
∼6
C
21
0.41
286
6.2
8.0
1.6
∼6
D
30
0.44
429
8.6
10.6
1.7
∼6
E
31
0.45
402
10.4
12.0
1.9
∼6
Mean
∼26
∼0.4
180
3
6
∼1
∼6
*
Bottom salinity – surface salinity (ΔS) / water column average salinity (ZS)
**
Apparent Oxygen Utilization (oxygen anomaly) = expected theoretical value as a function of
temperature and salinity) – observed value.
***
Typical value in surface waters: 2-4 µM
****
DIN ( N0X + NH4)
*****
Typical value in surface waters: 0.5-06 µM
Table 3: Evolution of mean dissolved oxygen and nutrients in the botton layer of the water column (depth >
10 m; salinity > 20, winds < 8 m/s) from mixing (by wind) to prolonged stratification conditions (modified
from Nagy et al., 2000; Nagy et al., 2002c).
Vertical stability (density stratification) isolates bottom waters from the atmospheric and surface
waters reservoirs of 02. Thus, degradation of CH20 consumes 02, produces C02, N03, P04
(remineralization) and triggers hypoxia and denitrification (conversion of N03 into N2).
Linear and non-linear relationships were calculated between the following variables: i) stratification
vs apparent oxygen consumption (A0U), ii) A0U Vs DIP (Dissolved Inorganic Phosphate - P04), iii)
A0U Vs N0X (Dissolved Nitrates plus Nitrites), and iv) QV Vs residue of A0U Vs N0X. They show
the effect of stratification over oxygen consumption (also called oxygen anomaly) in the deep water
column, between oxygen consumption and nutrient remineralization (N0X and DIP), and between
QV and N0X not attributable to oxygen consumption (residue A0U Vs N0X). This residue is supposed
to be related to pre-existent concentrations before remineralization and dilution or salinity gradient
(Nagy et al., 2000; 2002c).
These results are strong evidence of the role of wind and river flow over mixing and stratification
(ΔS / ΔZ) and how the stratification-destratification cycle (mixing state) govern biogeochemical
processes such as oxygen state, degradation (R) of CH20 and nutrient availabilty in deep waters
(suclinal environment), which in turn flows to the upper column (supraclinal environment) during
mixing (by wind) events (wind velocity greater than 8-10 m3 s –1; Nagy et al., 2002b.; Nagy et al.,
submitted). For shallow waters (depth < ∼6-8 m) tidal mix and resuspension is also important (Nagy
et al., 2002c).
Multivariate analysis of subclinal nutrient concentrations show that both [N] and [P] are mainly
explained by two independent variables: A0U and salinity, as well as the other primary nutrient –
N03-1 or P043- when equated, and secondary by temperature, with correlations > 0.8 (Nagy et al.,
2000).
These concepts are key for the understanding of the physical forcing of trophic state (P-R),
biogeochemical processes and symptoms of eutrophication.
18
3.2 Impacts, Vulnerability and Economic Scenarios of Coastal
Fisheries
3.2.1 Goal
To assess overall vulnerability, economic scenarios and adaptive capacity of the Coastal Fishery
System (CFS) in the Estuarine Front of the Rio de la Plata to cope with Global Environmental
Change.
3.2.2 Problem
An artisanal fleet exploit fisheries a few miles off the Uruguayan coast in the estuarine front (EF) of
the Rio de la Plata .
The location of the EF (Figure 17), therefore the accesibility of exploited resources, depends on
ENSO-related interannual variability of River Flow (Figure 18). Kiyú is the extreme river-ward site
of fishing during extreme La Niña events (1988-89 and 1999-00). San Luis is a desaggregation of
fishermen that migrated from western Montevideo (EF zone). Within the EF or frontal zone two
sharp color disconituities are observed, the main turbidity front (MTF) and secondary marine front
(SMF) (Severov et al. 2003, 2004), 140-180 down-river from Colonia on an average (see table 1).
Artisanal fishermen boats (Figure 17) and fishing are higly vulnerable to weather conditions
(winds), whereas the coastal fishery system is vulnerable to both climate and non-climate
constraints (Figure 20 and table 2).
Coastal communities have low to moderate adaptive capacity (Table 2).
The development of symptoms of eutrophication during the last two decades is deteriorating the
ecosystem posing new threatens to fishery livelihood.
Fig. 17: Frontal zone of the Rio de la Plata and location of sites of fishermen settlements (white). Urban areas of the
metropolitan Montevideo city (pink) (from Hernández and Rossi, 2002).
19
Salinity
River Flow
20
16
12
8
4
0
0
2
4
28
21
14
7
0
0
6
Sea surface anomaly (ENSO 3.4)
4
8
12
16
River Flow (m3/s x1000)
Fig. 18: Monthly relationships between ENSO SST 3,4 vs Uruguay River flow (left) and Uruguay River flow vs
salinity off Montevideo for the period January 1998 – Decemeber 2000 (from Nagy et al., 2002b)
Main divers of impacts, change and factors of vulnerability, adaptive capacity and management of
coastal fihseries, both artisanal (i.e., Pajas Blancas and Santa Catalina) and industrial fleets, in the
RdlP are:
3.2.3 Artisanal fishery
River flow: affect species availability in the fishing areas.
Weather (winds): limiting fishing trips.
Extreme events: affect bottom sediments (fishing zone).
3.2.4 Industrial fishery (coastal zone untill 50 m depth; not analyzed in
detail here):
Two objetive species: “croaker” and “sea trout”.
Change in spatio-temporal distribution.
•
Weather (frontal periods - winds): affect spatio - temporal resource availability.
•
time of search (higher economic cost).
In order to understand fisheries vulnerability it must be taken into acocunt risk and uncertainty,
and it’s sources in both environmental and management conditions (Hilborn & Peterman, 1996).
3.2.5 Risk and Uncertainty: sources, environmental and management
conditions.
•
variability in abiotic factors have an important impact on the abundance and spatiotemporal distribution of fish resources .
•
effects of ecological interdependencies.
•
fluctuations in costs and product prices that determine changes in exploitation intensity
and in the quantity demanded.
Variations in:
fishing effort determined by different fishing power and type of gear.
•
variability in the behavior of policy makers due to value judgments when taking
management decisions.
20
•
in the estimates of fish abundance.
•
in future environmental conditions.
•
in the response of users to regulations.
•
in future management objectives.
•
in economical, political and social conditions.
Environmental conditions show systematic patterns, e.g., periodic or linear trends. Thus, the
prediction of environmental future conditions is required, especially for resources sensitive to an
extreme degree to environmental changes.
Fig. 19: Typical artisanal fishing unit of Pajas Blancas CFS settlement (from Sención, 2003).
3.2.6 Pathways of response of human and natural systems to global
environmental change.
Main pathways of response of both human and natural systems of the coastal fishery system and
the livelihood vulnerability are presented in figures 20 and 21 respectively.
21
DRIVERS
CLIMATE CHANGE
ECONOMIC
and
+
and
ENSO VARIABILITY
POPULATION GROWTH
 Air Temperature
 Precipitation
Land Misuse / Cover Change
 Nutrient Point Sources
RIVER FLOW
⇓
IMPACTS
HYDROLOGIC ENVIRONMENT
 Water temperature
 Freshwater volume
 Salinity  Vertical Stratification
∆ Displacement of the Estuarine Front
 Nutrient Non-Point Sources
HUMAN SYSTEM
Change of fisheries accesibility
 Fish catch /economic benefit
Trophic Status Changes (symptoms of eutrophication)
 Algal Biomass (chlorophyll-a)
 Dissolved Oxygen
 Harmful Algal Blooms
∆ Ecosystem metabolism (p-r)
⇓
ADAPTATION
AUTONOMOUS ADJUSTMENTS
Salinity/oxygen changes
Fish Migration
ANTICIPATORY MEASURES
Adaptation Control Information System
⇓
Fishermen Migration
both fishing activity and settlements (from Western Monteivdeo to San Luis)
and
Increase in Catch
enhancement of appropiated weather / climate forecasting for fishermen
increase in the number of (good) fishing days
amelioration of legal and institutional conditions of fishermen communities
reduction of some vulnerabilities
Fig. 20: Pathways of response of fishermen (human system) and eutrophication (natural system) to combined
climate change, ENSO-related variability, and human drivers (modified from Nagy et al., 2003).
22
Figure 7. Causal loop diagram for fishery livilihood vulnerability (from Ponce 2004).
Fig. 21: Causal diagram loop of the coastal fishery system livelihood vulnerability (from Ponce, 2004)
3.2.7 Sensitivity and vulnerability of coastal fisheries
We estimated proxy variables - classified and valued respectively as low (1), moderate (2) and high
(3) - in order to assess social, economic, environmental and legal indicators of sensitivity of the
Pajas Blancas fishermen’s community. The sum of all indicators (non-weighted index of vulnerability)
suggest that the community is subject to moderate to high vulnerabilities (Table 6) but it seems to
be resilient. Determinant factors of vulnerability are strongly interrelated with the adaptive
capacity, autonomous fishermen’s adaptation and planned management options, which ultimately
reduce vulnerability.
Up to date, autonomous adaptation, good fishing skills and management practices have been the
key for the sustainability of the CFS under the current climatic, weather, environmental and
economic baselines (30-y trends). If vulnerabilities shown in table 3 are realistic, the CFS should be
more vulnerable under changing conditions in any of them. Main climate and non-climate
conditions shown below seem to be the main threaten to the sustainability of fishermen’s
community.
23
ENSO effect: warm phase/cold phase: rainy / dry
∆ Precipitation and ∆ River flow
•
Sea level rise and storm surges
•
South Atlantic Anticyclonic Southward displacement and ncrease in eastearly (E-SE) winds
(spring and summer).
•
Increase in fuel prize
•
Lack of social and legal organization
•
Regulations (Directorate of Aquatic Resources and Navy Coast Guard)
•
Lack of refrigeration
•
Conflicts with industrial fleet
Proxy variable
Social
Family
Education
Housing
Employment
Health
Social organization
Vulnerability
High (3)
Moderate (2)
X
X
X
X
X
Low (1)
X
Sub-total: 2.2/3
Economic
Boats
Engines
Fishing gears
Communications
Refrigeration
Catch
Prices
Net income
Sub-total: 2.0/3
Environmental
Climate - ENSO
Winds
Storm surges / Flooding
Eutrophication
Habitat loss
Sub-total: 2.2/3
Legal / Institutional
Laws
Territorial planning
Coast Guard controls
Conflicts with industrial fleet
Conflicts with neighbours
Legal organization
Sub-total: 2.5/3
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
24
Table 4: Assessment of the Vulnerability of the Coastal Fishermen Community. (Modified from Nagy et al.,
2003 and Norbis et al., 2004). Unweighted total Index of Vulnerability (IV) = 2.2 (scale 1-3).
3.2.8 Integrated climatic, economic and enviromental assessment,
scenarios and models
Only those strong ENSO events which effects last during the peak of the fishing period (i .e., El
Niño 1992, 1997, 2002 and La Niña 1989, 1999), seem actually impact fishing activity and net
income. Therefore, about one third of the peak fishing periods are bad in economic terms, when the
net income of fishermen is estimated to be reduced by ∼60% with regard to normal years (Figure 22,
Nagy et al., 2003; Norbis et al. 2004).
Fig. 22: Long-term fishing activity and net income (From Nagy et al., 2003).
The question addressed about the sustainability of coastal fisheries was thus empirically answered
because the fishing activity remains sustainable regardless of their (estimated) high vulnerability.
We suggest that their resiliency is (or was) due to:
•
the combination of planned and reactive adaptation measures to hydroclimatic variability
(i.e. migration),
•
good to very good fishing performance of most fishermen and
•
their (dominant) cautious behaviour (to avoid weather-related risks in spite of economic
losses), all of which reduced their vulnerability to remaining sustainable.
However, will they have the adaptive capacity to persist under increasing climatic and economic
pressures such as those occurred in 2002?
•
economic crisis,
25
•
increase in fuel prize,
•
a moderate El Niño year which decreased surface salinity at Pajas Blancas to close to zero
Figure 23 because of the seaward displacement of EF (Figure 24), and
•
increase in the occurrence of non-favorable wind conditions for fishing activity (> 8 m/s) as
presented in Figure 25 (Nagy et al., 2003; Norbis et al., 2004).
Fig. 23: Evolution of salinity at Pajas Blancas (October 2002 - May 2004). During 2002 salinity was zero during
the fishing period whereas during 2003 it was normal (from Norbis et al., 2004).
For this scenario, the assessment of vulnerabilities shown in table 3 seems to be more realistic,
suggesting the need to put more weight on climatic indicators because fishermen cannot cope with
them.
26
Fig. 24: Extreme seaward location of the estuarine front (red and yellow lines during El Niño event
(September-October 2002) (from Severov et al., 2004).
Figure 25 shows the occurrence of favorable and non-favorable wind conditions for fishing
activities from 2001 to 2003 (Nagy et al., 2003), according to the criteria established by Norbis (1995)
and Norbis et al. (2003) who demonstrated that Southern winds (SW to SE) > 8m/s are nonfavorable for fishing and most fishermen prefer not to risk fishing even at the beginning of the set
up of favorable conditions, usually losing one favorable day. Average wind speed in the region is 56 m/s but it increases to > 6 m/s during spring and summer time due to the prevailing SE winds
(Nagy et al., 1997; Escobar et al., 2004). It means that fishermen are both highly exposed and resilient
to develop their activity within a wind range close to the limit of 8 m/s. However, the overall
conditions during 2002 forced fishermen to change their no-risk behavior (Nagy et al., 2003; Norbis et
al., 2004).
Fig. 25: Frequency of wind favorable and unfavorable conditions and non-fishing days for the period September
2001 – March 2003 (from Nagy et al., 2003).
An economic estimation of fishing units capital and costs per year (boats, crew, engine, gears,
investment, maintenance and operation costs) was performed in order to build scenarios and
simple economic models of fishing activity at pajas Blancas (table 5).
U$D
b
N of fishing units
Investment capital
Maintenance cost / year
Operational cost / year
Chief boat salary / month
Crew salary / month
7500
500
4000
218
109
27
Nb
~31
Table 5: Economic estimation of fishing unit (from Sención, 2003).
The analysis of the fishing activity for the period 1998-1999 shows that the number of fishing boats
and capture increase during favorable days (Figure 26), when the number of daily sorties was 26-31
and capture per boat reached 40 boxes, suggesting that there is no resource limitation and that the
community follows the best fishermen.
Fig. 26: Clusters of number of fishing sorties, capture (Nb of boxes), and minimum and maximum Nb of boxes
during the fishing period 1998-1999.
Figure 27 shows an empirical scenario of fishing activity and productivity based upon the data
used to estimate the long-term yearly fishing activity gross income (see Figure 22) and the fishing
period 1998-1999 (a typical year) according to the data and results presented by Norbis and Verocai
(2003) and Norbis et al. (2003). This economic scenario was built for:
•
thirty fishing boats (artisanal fleet during the high fishing period), three durations of the
fishing period, three monthly number of fishing days, and three daily number of fish boxes
(~23 kg each one) which represents the variability observed on both the long-term since
1988 and for the 1998-1999 fishing periods activity (Norbis et al., 2004). This empirical
scenario is compared with the minimum (black line) and maximum (red line) captures
observed during the fishing period 1998-1999.
28
Fig. 27: Fishing activity and productivity scenario of Pajas Blancas coastal fishermen community (from Norbis et
al., 2004).
Summarizing, the variables considered in the empirical scenario are:
– 30 boats in each case and
•
fishing period (2, 3 and 4 months),
•
monthly fishing days (8, 14 and 17 days)
•
efficiency of fishing units (26, 38 and 46 boxes)
Thus, nine different combinations of i), ii) and iii) – or empirical scenarios – were built which
represent maximum (1) and minimum (9) fishing activity within the range of observed conditions
since 1988 – especially during 1998 /1999 – for each variable.
Six scenarios give captures greater than the maximum observed in 1998-99 and the most
performant are those based upon four and three months performant fishing activity: maximum
fishing days and boxes. It must be noted that these scenarios do not include captures during the
low fishing activity period (from February to September) as presented in Figure 22, when many
fishermen migrate seaward the estuarine front to San Luis (see Figures 1 and 17).
Both, the observations and the economic scenario suggest:
The longer the peak of the fishing period the greater the capture, which depends mainly on
hydroclimatic conditions (i.e. ENSO-induced EF location).
The number of fishing days per month is crucial and this is highly dependent on the occurrence of
Southern winds (wind-induced EF location and mixing status).
29
The sustainability of the fishing activity depends on several factors or the combination of them, for
which thresholds have been estimated: a) fishing activity must be) ≥ 15 days/month, b) fishing
period must be >2 months.
The number of boxes per boat / day does not seem to be a key factor. It is related to individual
performance and net income rather than the sustainability of fishermen’s community.
In case of an increase in climatic constraints only performant fishermen should mantain present
income.
Sea level rise and storm surges are a threat to fishermen coastal settlements.
It will be necessary to continue this analysis for at least two more years (from the past and/or
future) with different climatic, environmental and socio-economic conditions, as well as to
incorporate anthropological research.
3.2.9 Key findings
•
wind speed and rotations affect the artisanal fishery activity
•
limiting fishing trips. Favorable conditions during the peak fishing period (October to
March) are: winds of sectors N, NE and E and speed minor than 8,0 m/sec.
•
between October 1998 and March 2003 the favorable and unfavorable conditions showed
different trends with an increase of unfavorable conditions from September 2001. Nonfishing periods less than 15 days (threshold value) affect the economic subsistence of
artisanal fishermen.
•
performant fishermen (especially at Pajas Blancas site) have already adapted to past /
current climate variability in spite of bad years during El Niño and La Niña..
•
some fishermen communities (i.e. Santa Catalina community) and / or less performant
fishermen at Pajas Blancas community are highly vulnerable and their activity should be
unsustainable under increasing climatic, economic and environmental constraints if
adaptation strategies are not developed.
3.3
Impacts, Vulnerability and Coping Capacity of Trophic State
Changes (TSC)
3.3.1 Goal
To assess current and future vulnerability of the estuarine waters to express symptoms of
eutrophication.
3.3.2 Problem
The Rio de la Plata shows increasing symptoms of eutrophication (nutrient excess, increase in algal
biomass, hypoxia and increase in the occurrence of HABs) since the early 1980s.
3.3.3 Trophic state
Trophic state (TS) is the state of the ecosystem metabolism (system level Production minus Respiration
of organic matter) as a function of all organic material (CH20) inputs, both allochtonous and
autochtonous, usually based on Phytoplankton Primary Productivity (P), which is usually limited by
the turbidity gradient and nutrient availability in estuarine ecosystems (NCR, 2000; Pinckney et al.,
2004).
• Allochtonous inputs: Derived from outside the estuary and transported into by rivers, sewage,
30
•
atmosphere. They are divided into point-sources (i.e., sewage outfalls) and non-point sources
(i.e., runoff and atmospheric deposition).
Autochtonous inputs: Generated within the estuary by primary producers, benthic
regeneration and microbial processes.
Trophic states are usually divided into four categories, according to the load of CH20 to the system
(presssure and state) and /or according to the level of expression of the symptoms of eutrophication
(primary variables of response).
• Oligotrophic
• Mesotrophic
• Eutrophic
• Hypertrophic
3.3.4 The overload of nutrients: An environmental change on a global
scale
Human activity seems to have doubled the quantity of nitrogen recycled in the biosphere, and
more than doubled the rate of transfer of phosphorous to the ocean (Schlessinger, 1997; Rabalais and
Nixon, 2002).
The primary causes (pressures) of over-enrichment in Nitrogen (QN) and Phosphorous (QP) are
population increase, the use of synthetic fertilizers, and of the depositing of atmospheric N used in
the production of food and energy (Seitzinger et al., 2002). Nutrient flux is associated with three
drivers: landscape biogeochmistry, human intervention, and runoff (VQ), whereas the delivery of
nutrients to the ocean is associated with three variables: runoff, basin area and population (Smith et
al., 2003).
Most of these changes have occurred over the last thirty years. Many estuarine ecosystems receive
more nutrients than they can assimilate, but at the same time they are still the habitat of large
fisheries, and have other economic and aesthetic benefits. This is why the quantification of the
relations of the load of nutrients to coastal ecological processes is a scientific challenge (Rabalais and
Nixon, 2002; De Jonge et al., 2002).
There are present and future differences on the regional and latitudinal scale. The subtropical and
temperate zones of the southern hemisphere (20-45ºS) have a comparatively low percentage of the
area of hydrographic basins (∼9 x 106 km2 ), of the contribution of fertilizers, of sources and of the
export of Dissolved Inorganic Nitrogen (DIN), and the Rio de la Plata is the main source of DIN.
When it comes to considering continents, the export scenario for South America for the year 2050
(Business As Usual Scenario) would be nearly three times greater, exceeded only by Asia; on the
other hand, the export of Dissolved Inorganic Phosphorous (DIP) could decrease because of the
retentive effect of particles in reservoirs. Generically, the temperate regions export less than half the
N with respect to their total anthropogenic sources than do tropical regions, a phenomenon which
is not only explained by the distribution of the sources of N and the area of river basin, but also in
part by lower precipitation (Seitzinger et al., 2002), a factor which is not well represented in the
models.
3.3.5 Eutrophication and organic metabolism (P-R)
Eutrophication is the process by which a body of water is enriched with organic material when this
causes changes in that system. It is a cumulative global environmental change associated with
Nitrogen (N) and Phosphorus (P) excess, the drivers of which are the increase in population and
economic activities (e.g. the use of synthetic fertilizers; Seitzinger et al., 2002).
The excess of N and P from direct (point-sources) or diffuse (rivers and atmosphere) sources
stimulates in situ production of organic material (P) and the autotrophy - heterotrophy balance (PR) to harmful levels. This organic metabolism approximately follows Redfield’s stoichiometric ratio
(Gordon et al., 1996; eq. 1):
31
eq (1): -/+C106:-/+N16:-/+P1: ⇔ +/-O138
Rates of limiting nutrients inputs usually determine eutrophication and trophic state. Nitrogen is
usually the limiting nutrient, whereas phosphates and silicates (Si) may also be limiting in some
estuaries or at different times of the year. Therefore, estuarine ecosystems are impacted and
respond to external (extra-systemic) physical and human forcings such as increases in river flow
(QV) and temperature, land-use changes, fertilizer application, damming, sewage outfalls, and
nutrient loadings, by expressing symptoms of eutrophication
The occurrence of eutrophication effects or symptoms (excess algal biomass: chlorophyll-a, hypoxia
and harmful algal blooms-HABs) indicates when the system cannot cope with the available internal
and or external nutrient inputs (NCR, 2000; De Jonge et al., 2002). Organic metabolism of CH20 (P-R)
dictates the magnitude and direction of air/sea flux of bioactive elements (Gordon et al., 1996). The
greater the buoyancy (vertical stability) the greater are P (Lucas et al. 1999) and R (Rabalais et al.,
1999; Nagy et al., 2002b).. The assessment of the vulnerability of estuarine systems to TSC is under
development (NCR, 2000). The main factors in the expression of symptoms of eutrophication are:
•
flushing time (ft),
•
turbidity gradient (tg),
•
nutrient inputs (NI or QN) and
•
mixing state (stratification-destratification cycle: s-d) (De Jonge et al., 2002; Nagy et al.,
2002b).
3.3.6 Susceptibility
The susceptibility to express symptoms of eutrohication depend on both NI (NCR, 2000; De Jonge et
al., 2002) and the balance between QV and wind stress, which determine mixing state and transport
processes (EPA, 2001; Nagy, 2003, 2004). The susceptibility of estuarine systems to TSC depends on
the sensitivity and resiliency of the system as well as on climatic conditions which govern the
balance between buoyancy and mixing forces (Figure 28).
32
WIND
RIVER
TIDE
FLOW
MIXING
ES TU ARY
BUOYANCY
> QV → > Buoyancy ( ΔS / ΔZ) and > Winds and Tides → < Buoyancy (Mixing)
Fig. 28: Physical control factors of the susceptibility of estuarine systems to express symptoms of
change (Nagy 2003).
trophic state
3.3.7 Eutrophication pressures and trophic status in the Rio de la Plata
The Rio de la Plata is a large (3.1 x 106 km2; 3.6 x 109 m3), microtidal (amplitude -A < 2.0 m) coastal
plain system, which is rich in nutrients and trophically based on phytoplankton (López Laborde and
Nagy, 1999; Gómez-Erache et al., 2000; Nagy, 2000; Nagy et al., 2002c).
Because of its extension and morphological and environmental diversity, the RdlP can be divided
into tidal river and estuarine regions, which in turn can be sub-divided into a number of subsystems (Nagy et al., 2002c) with different depth, mixing state, trophic state, clarity and water
exchange. In the second half of the 20th century the basin was subject to an increase in human and
climatic pressures: nutrification, changes of use and erosion of the soils, increase in air and water
temperatures ∼0.8-1.0º C), precipitation and river flows (QV) respectively (∼20 to 35%), attributable
to global warming and to the increase in ENSO variability (García and Vargas, 1998; Nagy et al.,
2002b; Menéndez y Re, 2005) and the displacement towards the south of the subtropical Atlantic
anticyclone (Escobar, 2004). These changes have been greater during the last two decades (Bidegain
and Renom, 1998; Nagy et al., 2002d).
The tidal river is characterized by a moderate heterotrophy (source of C02): an excess of DIN,
especially ammonium of urban origin (mainly from Buenos Aires metropolitan area), and high
denitrification rate (Pizarro and Orlando, 1985; CARP, 1990; Bazán et al., 1996; Gómez-Erache et al., 2000;
Nagy et al., 2002c), with a concentration greater (> 20%) than the world average of 16%, slight oxic
deficit (<90% saturation) and cyanobacteria blooms. However, the expression of the symptoms of
eutrophication is limited by the turbidity gradient of the water (Pizarro and Orlando, 1985; CARP,
1990; Bazán et al., 1996; EcoPlata, 2000; Meybeck, 1982; Nagy et al., 2002c).
33
The estuarine region is globally autotrophic (sink of C02) and its nutrification is typical of non
impacted subtropical systems; however, it shows several symptoms of eutrophication: i) oxygen
deficit in the bottom layer (subclinal) in conditions of prolonged stratification (see Table 2), ii)
frequent HAB blooms in summer, and iii) high biomass, as well as high rate of denitrification
(Gómez-erache et al., 2000; Nagy et al., 2002c). The N/P ratio diminishes from >20 near the sources to
<15 further down, and <5 at the marine zone, due to dilution and losses of NH4+ due to assimilation
and /or adsorption) and of N031- due to assimilation and / or denitrificaton (Nagy et al., 1997; Nagy,
2000; Nagy et al., 2002c), that is to say, an evolution of the limitation of P by N (Table 6).
1-VF 2-VE QN / S
mM m3 y-1
x 1010
1-7
1500
QN /V C
B
O
FAN
Tidal River
QN DIN QP N / P Si / N Area (S)
mM m2 a-1
X 109
2,3 20-45 1 > 20 5-7 15
330
2
1
1
3
Frontal Zone
2,0 5-20
6
2-3
3300
470
1
2
2
2
16
2-1
750
120
1
1
2
3
Canal Oriental
Marine Zone
1,2
< 10 6-9
<6
< 10 3-6
<5
<5
5-9
Table 6: Loads, concentrations and ratios of typical nutrients, and degree of expression (1=light, 2= moderate,
3= high) of trophic indicators (C,B,O, HAB) in the Rio de la Plata: fluvial, frontal, Canal Oriental and
Marine (modified from Nagy 2002 and 2005).
During AIACC project we have conducted fieldwork at the Canal Oriental, the Frontal zone and
the Santa Lucía river estuary. We emphasized on some theoretical aspects such as the role of
climatic forcings and mixing state, which are known to control the expression of symptoms of
eutrophication (NCR 2000; De Jonge et al., 2002).
Recent researches (Smith et al., 2003; Calliari et al. 2005; Huret et al., 2004; Lappo et al., 2005; Nagy,
2005; López y Nagy, 2005; Ponce, unpublished report) suggest that TS indicators have increased (i.e
increase in typical nitrate and chlorophyll-a concentrations, and occurrence of cyanobacterial
blooms-Cyano-HABs) with regard to current baselines (1980-1989).
The RP shows an increasing trend of pressure indicators of TSC since the mid 1940s, and a shift of
state indicators during the 1980s (Nagy et al., 2003b; López and Nagy, 2005; Calliari et al., in press). For
example, eutrophic concentrations of nitrate (> 50 µM) and chlorophyll (>20 g/L) are found
during extreme floods (e.g., during El Niño 1983 or La Niña 1999 respectively; Nagy et al. 2002a,b).
Human and climatic drivers have indirectly altered TS by modifying the physical environment
(e.g., residence time, local warming), and / or stimulated the development of new symptoms (i.e.
bottom water hypoxia under prolonged stratification periods and HABs), and these drivers are
expected to increase in the next few decades. Therefore, an increase in QV should increase the
vulnerability.
3.3.8 Indicators of susceptibility, impact and vulnerability
We are in need to develop indicators of susceptibility (e.g. ft, residence time of water-RT, buoyancy
and mixing status) and TS for both cross-system and long-term comparisons as well as for the
assessment of the impact of the degree of nutrient excess in estuaries (NCR, 2000; De Jonge et al.,
2002: EPA, 2001). Some indicators were developed for fresh and estuarine waters of the Uruguayan
coastal zone and watersheds (Nagy et al., 2002b, 2004; Nagy, 2003; Nagy and Ferrari, 2003) as
presented in Figure 29. The main variables considered are:
•
susceptibility (e.g. ft, RT, buoyancy and mixing status).
•
drivers (population density, fertilizer use, point sources and river flow).
•
pressure (N, P, and Si load and gradients).
34
•
state or causal variables (e.g. [N, P]).
•
response / impacts or symptoms (Chl-a), [02]HABs occurrence, nutrient ratios (N/P and
N/Si) and species change (Officer and Ryther, 1980; Turner, 2002).
DRIVERS
PRESSURE
STATE
/
IMPACT and / or RESPONSE
Changes in
Socioeconomic╠► > Nutrient Load
> N,P
> HABs
Trophic State, P-R,
>Chl a
╠► Nutrient ratios and
Climatic
╠►> Water load
> Stratification
< O2
Biodiversity
Fig. 29: d-PSI Framework (modifed from Nagy, 2003).
3.3.9 Causes and symtpoms of eutrophication in the Rio de la Plata
Even if nutrient inputs to the Rio de la Plata are well below the figures for developed countries,
estimated by Nagy (2003) as being ∼330 and 120 mM m3 y-1 for the tidal river and marine zone
repectively (based on data from Pizarro and Orlando 1985, Nagy 2000, Menéndez et al 2002), they are
higher than they were in the past (e.g. estimated for 1950) because of:
Increase in population and agricultural intensificaton (sewage, fertilization, irrigation,
soil erosion, leaching) (López and Nagy 2005)
land-use,
Increases in precipitation and river flow (> 30%).
Persistent stratificacion (over several tidal cycles to weeks during fall) (Nagy et al 2002b) and
Low tidal mixing and (horizontal) excursion (Nagy, 2000) determining the development of
symptoms of eutrophication (as defined by Bricker et al. 1999; 2003, NCR 2000, EPA 2001):
Low dissolved oxygen concentration in bottom waters (subclinal environment).
Supraclinal eutrophic levels of chlorophyll-a (e.g. > 20
g l-1).
HABs occur since at least 1980, showing an increase in frequence during the last decade.
Eutrophic nitrate levels (e.g. > 50 µM) during severe/extreme floods (e.g. El Niño 1983, Nagy et al.
2002a,b), and an increase in typical mesoeutrophic values over the last few years.
Summarizing, the Rio de la Plata is highly susceptible to express symptoms of eutrophication
because of low tidal mixing and mixing status (mix is driven by winds) and high RT, and
moderately eutrophied because of nutrient load (NI), NI / estuary volume ratios, total normalized
nitrogen load-TNNL (= N input x Area x mixed layer depth / RT, expressed as µM), internal
sources (remineralization and low dissolved oxygen concentrations in bottom waters). Redfield
stoichiometry varyies from 6 to 10 (Nagy et al. 2002b), and denitrification (sink of N) reduces
eutrophication danger provided that present oxygen levels be mantained; Nagy et al 2002a,b).
3.3.10
Harmful algal blooms (HABs)
Harmful and Noxious Algal Bloms (HABs) events have a great economic impact because they affect
the commercialization of mollusks and fish, and tourism in Uruguay. The first episodes of toxic
HABs on both the Argentine and Uruguayan coasts occurred in 1980 (Yentsch 1982). Since that year
they have occurred every spring on the Argentina platform, while on the Uruguayan coast they
recurred in 1991, and every year since up the present time (Carreto et al. 1998; Ferrari 2002).
The Paralytic Shellfish Poisoning (PSP) producing species are Gymnodinium catenatum and
Alexandrium tamarense. The former is registered in summer and the fall (Méndez and Ferrari 2002)
and the latter at the beginning of spring (Méndez et al. 1996; Brazeiro et al 1997). Gymnodinium
catenatum was noted for the first time in the area in the summer of 1992, and since then every
summer-fall its presence and toxicity has appeared. The greatest development of the blooms of this
35
species occurs in the warm waters of summer, and given the presence of cysts in the sediment
(Méndez 1995), the start is attributed to the re-suspension of cysts in the sediment and to these
temperature conditions. A. tamarense develops in the south and is associated with subantarctic
waters of the Argentine platform, and it is carried by the currents to Uruguayan waters depending
on the reduction in the discharge of the tributaries of the Rio de la Plata (Méndez et al. 1996),
particularly of the Uruguay River (Nagy et al 2002b).
The first diarrheic intoxications in Uruguay occurred in 1990; they were due to the presence of
Dinophysis acuminata, and then diarrheic episodes also occurred in 1992, 1994 and 1996. However,
the presence of Dinophysis is variable in all seasons of the year (Ferrari et al., 2000).
The diatoms of the genus Pseudo-nitzschia, present on the coasts but never associated with toxic
episodes, manifested it in December 2001, causing a peak below the limit level of amnesic toxin
(Medina et al., 2002).
Cyanobacteria have multiplied in recent years, although their presence had been recorded for a
number of years before; the first appearance of Microcystis aeruginosa in the Rio de la Plata was in
1982 (CARP, 1990). This species is very persistent in the summer months, especially on the coasts of
Montevideo and Colonia, and its bloom produces extensive green stains which dye the water as if
they were paint. Toxic blooms occurred in 1997 and 1999 (De León and Yunes, 2001). In the summer
of 2001, the massive bloom all along the whole coast of the Rio de la Plata was accompanied by
other species of Microcystis which had not been noted before (Ferrari and Sienra, 2002).
Diatom Aulacoseira granulata and the cyanobacteria Microcystis aeruginosa, both associated with
river discharge, are indicators of two coexistent trophic status on different time and geographic
scales (López and Nagy, 2005):
(1) alternated mesoeutrophic and
2) persistent eutrophic, related to combined lotic-lentic communities, the former being typical of
the annual cycle and the latter of the warm period (late spring to early autumn).
This distribution pattern covers the lower basin and the north coast of the Rio de la Plata,
especially associated to River Negro and Uruguay discharges (O’Farrell and Izaguirre, 1994; Bonilla,
1997). To be able to understand and predict the HAB blooms, it will be necessary to carry out
connected studies of climatic events on a macro scale, of ENSO events, the discharge of the Paraná
and Uruguay rivers, the location of the frontal zone of the Rio de la Plata and of the subtropical
convergence front (Ferrari, 2003).
Table 7 shows an example of impact matrix of HABs occurrence developed by Ferrari and Nagy (
2003) for the Uruguyan coastal zone of RP for the decade 1991-2000. Four indicators were estimated
and aggregated: i) intensity of HABs (cells/L), ii) persistance (months), iii) extension along the coast
(% of coverage) and iv) toxicity (toxin concentration from low to very high). Both freshwater
(cyanobacteria HABs) and estuarine/marine species were considered. HAB Index = Toxic Species
Index + Noxious Species Index
Prevailing
2
Indicators
0
1
Intensity (cells/liter)
0
102
103
104
105
Persistance (months)
0
0.25
0.75
1-6
Extension (% of coverage)
Toxicity ( concentration)
0
0
10
low
25
moderate
50-75
high
>6
>75
very high
2
3
Extreme
4
Table 7: Aggregated impact matrix of HABs (both fesh-and estuarine waters) in the Uruguayan coastal zone
of the Rio de la Plata for the period 1991-2000 (from Ferrari and Nagy, 2003).
36
A second aggregated impact matrix was then built in order to take into account the occurrence of
the four main HAB species weighted from absence (0) to very high (4) according to the criteria
defined in table 1. Weights of the HAB species were summed and ranked and ranked from 0 to 100
or very low to very high, respectively. Weighting criteria were based on both the literature (EPA,
2001) and local occurrence according to expert judgement of the authors (Table 8). The SST 3.4
index – which is well correlated with QU - is reported on annual basis (from March to February).
Year
1990-91
1991-92
1992-93
1993-94
1994-95
1995-96
1996-97
1997-98
1998-99
1999-00
Average
SST 1
3.4 Alexandrum
tamarense
0.3 3
1.0 2
0.4 2.75
0.4 1.25
0.6 2
-0.4 3
-0.3 1.25
1.8 0
-0.7 1.25
-1.3 1.0
0.2 1.75
2
Gymnodium
catenatum
0
3
2.75
2.25
2.25
2.25
1.5
2
1.25
1
1.83
3
Dinophysis
acuminata
0
2
0
1.5
0
1.5
0
0
0
0
0.5
4
Mycrocistis
aeruginosa
0
2
0
2.75
0
0
3
0
2
0
0.98
Σ
Index
0-100
Impact
3
9
5.5
7.75
4.25
7
6
2
4.5
2
4.7
21
64
39
55
30
50
43
14
32
14
36
Low
High
Low
Médium
Low
Médium
Medium
Very low
Low
Very low
Low /medium
Table 8: Aggregated impact index of HABs for the Rio de la Plata (1991-2000; from Ferrari and Nagy, 2003).
Finally, these indicators were weighted taking into account their impacts on three sectors: i) Human
Health (H), ii) Economic activity (Ec) specifically mollusks consumption, and iii) Environmental
Health (Ev) according to the expert judgement of the authors. Coefficient weights were 0.75, 0.50
and 0.25 for H, Ec and Ev respectively, which were multiplied by the values reported in table 5.
Thus, a weighted aggregated impact index of persistence /extension /toxicity (IPET) was built
(Table 9). An impact coefficient was assigned for each of the four species. Relative impact of each
indicator (IPET from 0 to 1) is shown for each species and sector. Extreme values are toxicity of
Gymnodinium for H and intensity of Dinophysis for Ev.
Weighted Index for each sector (0-1)
Species
Gymnodinium
Alexandrum
Microcystis
Dinophysis
0.50
0.42
0.33
0.22
Health: 0.75 Economic activity: 0,50 Environment: 0.25
T: 0.37
T: 0.25
P: 0.13
E: 0.32
P: 0.21
E: 0.11
P: 0.25
E: 0.17
T: 0.08
I: 0.19
I: 0.13
I: 0.06
Table 9: Weighted aggregated impact index of HABs (IPET) for each species and sector in the Northern coast
of the Rio de la Plata (1991-2000; from Ferrari and Nagy, 2003).
The overall impact of HABs occurrence during the studied period was low to medium, with only
one high impact year (1992) and two very low impact years (1998 and 2000), which coincide with
strong ENSO events (1997-98 and 1999-2000 respectively). However, the only one species that
reached high values in 1991 and 1993 (the highly toxic Alexandrium tamarense) was related to both
the northward displacement of Malvinas current – where Alexandrum is present – and low QV
(Méndez et al., 2001); especially because of extreme low QU (Nagy et al., 2002b), as well as in 1996 when QU was very low-. Usually, both drivers are associated with El Niño and La Niña years
respectively, which reduces the vulnerabilty of RP to suffer the presence of Alexandrium blooms.
Up to date they have occurred during early spring time – when Malvinas current often reaches the
mouth of the RP advecting cold waters and Alexandrium into the estuary if QV is low- but should
be potentially dangeorus to H if they should occur during summer time.
37
3.3.11
Coping capacity and resiliency to trophic state changes
Even if there is not a clear pattern of HABs occurrence with ENSO ST 3.4 index, some examples
such as the occurence of Alexandrum in 1991, 1993 and 1996, the relatively high index of El Niño
multiyear event (1991-94), and extreme events of the years 1998 and 2000 suggest some
hydroclimatic control. Recent years (2001 and 2003, not shown here) have shown a marked increase
in Cyano-HABs (López and Nagy,2005) at intensities higher (> 3) than those found during the past
decade and this seem to be the main problem for future years. Strong ENSO years coud stimulate
cyano-blooms in the RP, the former by advecting freshwaters (from River Uruguay) and the latter
by decreasing the ft of water and particles. The coping capacity thresholds for TSC as a function of
QV extremes associated with El Niño (>32 x 103 m3/s) and La Niña (<16 x 103 m3/s) are synthesized
in table 10 and Figure 30.
3
River Flow
thresholds
QV
QU
Wind-related
thresholds
x 103
m3 s-1
< 16
< 2
m s-1
State
>10
Mixing of shallow < 6
water column
(< ~10 m)
Mixing of bottom < 8
waters (> ~17 m)
>13
Eutrophic
Eutrophic
x 103
m3 s-1
> 35
> 12
m s-1
State
Impacts
Eutrophic
Eutrophic
[Chl-a], Cyano-HABs
[Chl-a], Cyano-HABs
Prolonged stratification of
shallow water column
> p-r
Prolonged stratification of
deep water column
Hypoxia
Remineralization of N,P
Denitrification
< Fishing activity
Displacement of EF
>8-10
Table 10: Coping capacity, resiliency, ecosystem state and impacts as a function of river flow and wind
thresholds (Y: A*X* functions); (based upon data from Norbis, 1995; Nagy et al., 2001; Nagy et al., 2002c;
Nagy et al., submitted).
38
QV
>N, P, > N/P >dS/dZ
< Flushing (ft)
> HABs
Vulnerability Threshold ( > 32.000 m3/s)
Coping
grange
4
Vulnerability Threshold ( < 16.000 m3/s)
-
> Chl a
< dS/dZ
> ft
> HABs
-
Fig. 30: Conceptual coping range of trophic state changes ( N, P, N/P, buoyancy, flushing time, HAB5s, Chl-a) as
a function of river flow variability (modified from Nagy, 2003).
3.3.12
Susceptibility in microtidal systems
The processes of mixing and transport in coastal plain systems are dominated by the tide (A), river
flow (QV) and winds (W) as presented in Figure 30 and Tables 3 and 11. The balance between these
forces and morphology determines the spatial salinity and turbidity gradients, and mixing state,
determining factors of organic metabolism (P -R) and the degree of expression of the symptoms of
eutrophication to the load of nutrients (Table 11). Microtidal systems have a low capacity to mix,
which depends on the wind, and in them QV is the “master variable” which controls buoyancy
(dS/dZ), nutrification, RT, stratification and gravitational circulation, and salinity (EPA, 2001;
Monismith et al., 1996); at similar QN these systems present values of B, p and r greater than in
macrotidal systems (EPA, 2001).
Type Mixing
forces
Mixing
energy
Salinity
gradient
Mixing Turbidity Bottom
index
Stability
Low
Width /
Depth
Ratio
Low
A
QF
Long/Vert
>1
B
QF, A
Medium
Medium
Long/Vert
<1/10
Medium
Good
Very High Chesapeake
C
A, W
High
High
Long/Lat
<1/20
High
Fair
High
39
Very High Low
P
Low
Example
Mississippi
Delaware
D
A, W
Very High Very High Lateral
?
High
Poor
Medium
A
QF , W, A High
High
<1/10
High
Poor
Low
B,A
QF , W, A Medium
Very High Lo/Ver/Lat <1/10
Medium
Medium Very High RP Front
A
QF , W,
Low
Medium
Low/Med Good
B
W, QF
Medium
Very High Lo/Ver/Lat < 1/10
no
Long/Vert
<1/20
Low
High
Medium High
RP FM
RP Plume
RP Ext
Table 11: Characteristics of the classification of coastal plain estuaries (EPA, 2001) and it’s appliccation to
the study of trophic state of the Rio de la Plata.
3.3.13
Summary of determinant factors on the susceptibility to
expres symptoms of eutrophication and current trophic state scenario
of the Rio de la Plata.
The comparative study of microtidal systems indicates that there are three main factors which
affect susceptibility (EPA, 2001; Bricker et al., 2003), all of which are very dependent on flow (QV).
1- dilution (Q/V) and residence time (RT) of the fresh water (Q/VESTUARINE WATER).
2- the ratio of the nutrient load QN by area (S) and volume (V).
3- the stratification-destratification cycle (López Laborde and Nagy, 1999;EPA, 2001;).
Dilution (Q/V), residence time (RT) and the QN /S and QN /V ratios are proxy variables of the
capacity of the system to receive and assimilate nutrients. They are very useful in low volume (V)
and vertically mixed systems, and can be well applied in the tidal river (Table 10). In stratified
systems, it is better to use suprapicnoclinal volume (VESTUARINE WATER, EPA, 2001).
Mixing state is controlled by QV, the wind (W) and the tide (A); the greater the ratio Q/V, the
greater the river predominance, e.g. the tidal river and the Canal Oriental of the Rio de la Plata
(Nagy et al., 2002c). Stratified systems are susceptible to subclinal oxic stress (Rabalais et al., 1999)
due to the fact that the downward transport of oxygen, nutrients and plankton is limited (>R),
determining greater RT in the euphotic zone (usually in the supraclinal environment), greater algal
development, productivity and assimilation of nutrients (>P) (EPA, 2201; Rabalais et al., 1999; Cloern,
2001).
Oxic stress is not only due to metabolic increase but also to the vertical stratification of density (>
ΔS and / or > ΔTemperature), long RT, low tidal mix, and a high ratio of the area of the basin (BA) to
the volume of the estuary (Cloern, 2001); the first two factors controlled by QV, are to a greater or
lesser extent applicable to the Rio de la Plata. If stratification persists through a number of tide
cycles (Simpson et al., 1990) the organic metabolism diminishes, regulated by the turbulent mix
introduced by the wind in function of its intensity and duration, by buoyancy (dS/dZ) and by
depth. Therefore, deep regions (> ~15m) are more susceptible than the shallows (< ~10m) as the
subclinal layer remains for weeks without mixing completely. This condition is typical of the end of
the fall and the start of winter (April-August), when the wind is less intense, the QV is greater, and
the salinity front is located down-river at greater depth (Nagy, 2000; Guerrero et al., 1997; Simionato et
al., 2001; Nagy et al., submitted).
In late spring and the start of summer (November-February) trophic susceptibility is controlled by
the increase in temperature and solar radiation, and consequently of B and P – R, a lower QV (except
in the El Niño years) and the predominance of onshore winds (E-S); as these are the ones which
have the greatest effect (Nagy et al., 1997; Guerrero et al., 1997; Simionato et al., 2001). All this favors
the move up-river of the salinity front (to less depth), and less vertical difference in density,
facilitating the upward flow of nutrients. On the interannual scale, a combination of these seasonal
conditions would predominate, with interaction of buoyancy and the mix, which have increased
due to the increase in QF, temperature and of the frequency of onshore winds in the last three
decades respectively (Nagy, 2000; Bishcoff, 2002; Escobar, 2004). This balance would also control the
source of “new” nutrients from the subclinal environment, autotrophy (p) in the euphotic layer,
and, probably, the ratios of nutrients. Although neither these balances nor their effects have been
40
quantified, the increase in HAB blooms in the Canal Oriental could be connected with the
development of these indicators.
3.3.14
Reflections on the use and application of trophic indicators
in the Rio de la Plata
The use of trophic indicators is complex and ambiguous. It depends on time-scales, e.g.
phytoplankton responds to changes in nutrient concentrations (Δc) in hours to days while the
recycling of bioamss (B) in nutrients takes days to weeks. Besides, nutrification associated with
greater QV might not develop the expression of symptoms of eutrophication in the system due to
the lower RT and the greater export of nutrients (EPA, 2001). Two indicators which combine many
of these concepts for systems limited by N are:
i) the export rate (ΕN), or percentage of N which leaves the system without in situ losses (EPA,
2001) .
ii) the total normalized load of nitrogen-QnN (EPA, 2001).
The export rate (in %) or delivery is estimated from input (QN) and output values and / or dilution
curves (plot of salinity Vs nutrients). Residence time is a control factor for this rate: the greater the
RT the less E (> in situ losses); if RT is lesser than one day the symptoms of eutrophication are not
expressed since the phytoplankton does not double independently of nutrification (EPA, 2001). ΕN
varied in the Rio de la Plata between 5 and 20 % for a RT of around 1 month (2 to 6 weeks; Nagy,
2000).
The normalized total nitrogen load is an index of the potential for eutrophication expressed as c
(uM), and is estimated from QN, S, Z and RT (QnN= QN x S x Z/RT); in stratified systems supraclinal
Z is used. Table 14 shows QnN for the subsystems considered.
(sub) System
Area
Z
QDIN
RT
oxic status
Mixing status
E (%) QNn DIN
uM
uM
Name
103 km2 m
mM m-2 months OK-H-A
Baltic
374
55
217
250
Hypo/Anoxia
Stratified
-
81
Chesapeake
11
6
938
8
Anoxia
Stratified
-
98
Gulf of Mexico
20
30
6500
6
Hypo/Anoxia
Stratified
-
107
Tidal River-RP
15
5
1500
0.9
OK
Homogeneous
≥ 80
22
30-45
Frontal Zone-RP 6
8
2700
0.3
OK/Hypoxia
Stratified
≥ 80
25
5-20
Canal Oriental-RP 5
17
800
0.5
OK/Hypoxia
Highly stratified
Marine Zone-RP 14
14
1800
0.6
OK/Hypoxia
Stratified
>70
13
<5
Table 12: Nitrogen load, rate of export, mixing status and subclinal oxic status (OK, Anoxia-A, Hypoxia-H)
of subsystems of the Rio de la Plata and other stratified estuarine systems (based on EPA, 2001; Nagy et al.,
2002c).
The estimates of QnN are comparable with the mean concentrations of the four subsystems (Nagy et
al., 2003c), in particular for the tidal river and the frontal zone, while they are underestimated and
overestimated in the Canal Oriental and marine zone respectively. This seems to be due to greater
uncertainty in the estimating of input and of RT. These values suggest a mesoeutrophic system. In
the stratified sub-systems, the internal source of new nitrates come from the subclinal reservoir
(Nagy et al., 2002c), estimated, for the Canal Oriental, as being of the same order of magnitude of the
supraclinal. Compared with an empirical model of the fractions exported aa a function of time of
residence in world’s estuaries, a similar behavior in the tidal river (<1 month and E ∼0.75) can be
41
seen, while in the estuarine region (RT ∼0.3-0.5 month) it is somewhat less (E≤0.6) than the model (>
0.7), which would be explained by losses through denitrification and the temporal accumulation in
the subclinal reservoir (Gómez-Erache et al., 2000; Nagy et al., 2002c).
3.3.15
Oxic status and vulnerability of the fish habitat
Oxic deficit affects the habitat of fish and their reproductive location; therefore, it is preferable to
consider the concentrations which cause biological stress in fish as hypoxia, that is to say ≤50% of
oxygen saturation (Breitburg, 2002). These concentrations do not prevail in the shallow zones of the
Frontal Zone (Nagy et al., 2002c) where its main resource, the white croaker spawns in springsummer (Vizziano, 2003; Vizziano et al., 2003) and its frequent occurrence in the present scenario
does not seem plausible.
3.4 Sea Level Rise and Coastal Vulnerability of the Western
Coast of Montevideo
3.4.1 Introduction
The western coastline of Montevideo (~80 km including fishermen settlements, Santa Lucía river
estuary and mouth, beaches and wetlands) was previously defined by several qualitative
assessments as one of the most vulnerable of the country to sea level rise-SLR (Table 13).
This coast is unique because it is subject to fluvial, estuarine and marine forcings (tides, storm
surges, river flow, drift currents and changes in salinity) due to its location within the transition
from fresh- to estuarine waters (Nagy et al. 2004). The soleley long-term tide-gauge record in
Uruguay is located within this coastal section of Punta Lobos (Figure 31). The rate of increase was
0.11 mm/y (within the world range, IPCC, 2001). During the last 15 years this rate was ≥3 mm/y
and the extremes were associated with strong La Niña-1989 and El Niño-1998 respectively (from
Nagy et al., 2004a).
Sea Level Trend at Punta Lobos, Montevideo (1971-2000)
The trend was 0.1 mm/y
115
y = 0.1268x + 96.768
R 2 = 0.041
110
105
100
95
90
85
1
2
3
4
5
6
7
8
9
10
11
12
13
14
Years
15
16
17
18
19
20
21
22
23
24
25
26
1971 - 2000
Fig. 31: Sea level rise in Montevideo during the period 1971-2000 (from Nagy et al., 2004a).
42
27
28
29
30
Sector
Low
People affected
Moderate
ete
High
X
People at risk
X
Biodiversity (e.g., wetlands, bird habitat)
X
Capital at risk / Infrastructure
X
Coastal Fisheries
X
Tourism
X
Table 13: Synthesis of previous cualitative assessments of the vulnerability of people, sectors, and systems in
the western coast of Montevideo (from Kokot et al., 2004, based on Saizar, 1997; Nicholls and Mimura, 1998;
EcoPlata, 2000; OECD, 2004; UCC, 2004).
3.4.2 Dynamical factors that increase vulnerability to SLR are:
Southern winds (especially those from the WSW to the SSE) increase observed amplitude (1.0 m)
and produce storm surges and floodings (3.0 - 4.0 m) which when combined ravage the coast
(Lorenzo and Texeira, 1997; Pshennilkov et al., 2003; Nagy et al., 2004b). An example of this occurred in
February 1993.
Strong ENSO-related observed fluctuations of QU and QP (regional factor) and QSL (local factor) that
increase or decrease observed amplitude (+/-10 cm) on annual basis (Nagy et al., 2004b).
The former is common to most world’s coastlines and the latter is a particularity of the coasts of the
RP due to its river-dominated regime (controlled by winds over synoptic timescale).
3.4.3 Factors of vulnerability
We used a quantitative index of vulnerability (Gornitz, 1990, Gornitz et al., 1997; Shaw 1998) which
is built on 7 indicators shown below where vulnerability decrease to the right.
•
Height: from –0.5 m to 5 m: low lying areas (-0.5 m) are highly vulnerable to
•
moderate SLR (0.3 m) and storm surges. Of particular concern are wetlands.
•
Lithology: Hard rocks / Sedimentary rocks / Sediments / Unconsolidated
•
sediments
•
Geoforms: cliffs, wetlands, sandy beaches, rocky shores.
•
SLR: Over the past 100 years SLR was 9 cm, below both world average (15 cm) and Buenos
Aires (17 cm; Barros, 2003). However it shows an increasing rate since 1971 (Figure 22).
•
Coastal retreat: stable / low / moderate
•
Tidal amplitude: 0.5 m (or 1.0 m due to wind).
•
Wave energy: ~2.0 m (estimated).
Thus the vulnerability was objectivley classified as low, moderate and high for 24 boxes along the
coastline (Table 14 and Figure 32). The western sector and wetlands are highly vulnerable to SLR
and SSE - WSW storm surges.
43
COASTAL VULNERABILITY
Very low
Low
Moderate
High
Very high
VARIABLES
1
2
3
4
5
1. Height (m)
>30
6-10
0-5
21-30
11-20
2. Type of
Rock
High grade
plutonic,
Volcanic and
high grade
metam. rocks.
Metamorpp. Majority of
rocks
Sedimentary
rocks
Sedimentary
rocks
Not very
Consolidated
sediments
Unconsoli
-dated
sediments
3. Geoform
Fiords,
high cliffs
Interm.
and low
cliffs
Beaches,
Beaches
on
littoral
platform
Barriers,
deltas,
tombolos
Tidal
plains,
marshes ,
wetlands
> -50
-50 – 20
-19 +20
+21 - +40
> +40
>+0.1
accretion
0
stable
-0.1 –0.5
erosion
-0.6 –1.0
erosion
>1.0
erosion
6. Tidal range
(m)
<0.50
0.5 – 1.9
2.0 – 4.0
4 -6
7. Maximum
height of wave
in a year (m)
0-2.9
3.0-4.9
5.0-5.9
6.0-6.9
4. Sea level
(cm / 100 y)
5. Displacement
of coastline
(m/y)
>6.0
Table 14: Coastal vulnerability matrix for the western coast of Montevideo (from Kokot et al., 2004).
44
Fig. 32: Coastal vulnerability of western Montevideo and Santa Lucia coastal zone.
Red colored low-lying area is a continuum of sandy beaches (from Kokot et al., 2004).
45
3.5
Santa Lucía River Estuary
3.5.1 Hydrology
The Santa Lucía river estuary and coastal zone (SL) is the main low-lying coastal subsystem of the
Rio de la Plata’s northern coast (Figure 33). This system is highly nutrified (mostly N from fertilizer
application) and rich in biodiversity (associated with sandy beaches, salt marshes and wetlands,
EcoPlata, 2000; Caffera et al., 2004; Nagy et al., 2004) and supplies most of drinking water to
Montevideo and surroundings. The mouth (estuarine zone), located close to the estuarine front, is a
subsystem of the RP, from where it receives salt water a few months of the year.
Fig. 33: Main Santa Lucía River basin, southern Uruguay, and the estuarine front.
Interannual variability of river discharge (QSL<0.02 to >1.8 103 m3s-1, average: ~0.10 x 103 m3 s-1) as
presented in Figure 34 is ENSO-related in the middle basin from August to February, especially
from October to December, which coincides with the peak of fishing capture in the adjacent EF.
Nevertheless, this relationship was not not clear on yearly basis for two of the strongest events (El
Niño 1997 and La Niña 1999 respectively), when the influence was very strong on seasonal basis.
Both an increasing trend (> 25%) and a relationship with ENSO-related variability (El Niño: 1983,
1993 and La Niña 1989, 1996, 2000) are observed.
During floods QSL decreases the salinity and increses both the nutrification and stratification
(buoyancy) of adjacent waters of the Rio de la Plata (Caffera et al., 2004) close to the EF, which
should favor C02 fixation (P) via photosynthesis. The historical daily maximum was 4.1 x 103 m3s-1.
Such as a strong relationship with ENSO was not expected because previous works (Bidegain and
Caffera, 1989) indicated that it’s signal was relatively weak in southern Uruguay. River flow at the
middle basin follows yearly precipitations at Florida city a few tens of km upstream. Monthly
precipitations at Florida (1990-2003) are shown in Figure 35. Both precipitations and QSL are greater
than the average from February to April and from October to December (when ENSO influence is
maximum) and decrease from June to August (austral winter). Average yearly precipitation during
recent years (1997-2003) is 7% greater than the climatic reference (1961-1990).
46
m3 / s
Santa Lucia River yearly discharge 1979 - 2003
200
180
160
140
120
100
80
60
40
20
0
2003
2001
1999
1997
1995
1993
1991
1989
1987
1985
1983
1981
1979
Fig. 34: Santa Lucía River yearly discharge (1979-2003).
The influence of El Niño is strong in October - November and weak in February (Table 15 and
Figure 36), whereas La Niña influence is strong in October and February, and weak in January.
Fig. 35: Monthly average precipitations at Florida in the middle Santa Lucia basin.
47
ENSO phase
El Niño (EN)
Neutral (N)
La Niña (LN)
El Niño
Neutral
La Niña
El Niño
Neutral
La Niña
El Niño
Neutral
La Niña
El Niño
Neutral
La Niña
EN average
N average
LN average
Month
October
October
October
November
November
November
December
December
December
January
January
January
February
February
February
DHR > 0.75
0.33
0.28
0.03
0.52
0.36
0.13
0.38
0.24
0.12
0.19
0.24
0.37
0.08
0.28
0.37
0.30
0.28
0.20
EN-November
LN- December
Maximum
Minimum
6
DHR > 0.50
DHR < 0.25
0.68
0.12
0.55
0.17
0.08
0.69
0.68
0.09
0.52
0.21
0.22
0.52
0.67
0.04
0.45
0.16
0.16
0.28
0.54
0.07
0.46
0.24
0.48
0.20
0.45
0.14
0.57
0.18
0.32
0.62
0.60
0.09
0.51
0.19
0.25
0.46
EN-Oct/November LN Oct/February
LN-October
EN-December
Table 15: Daily river heights (DRH) during ENSO (October/December) and ENSO +1 (January/ February)
years (1979-2003) in the middle Santa Lucia Basin (modified from Caffera et al., 2004).
Greater>0.75 (25%)
High>0.50 (50%)
Low Water < 0.25 (25%)
- Heights discrimination according to ENSO R 11 Bridge - October
0,3359
El Niño
0,6797
0,1250
0,2839
Neutro
0,5484
0,1677
La Niña
0,00
0,0323
0,0806
0,10
0,6855
0,20
0,30
0,40
0,50
0,60
0,70
0,80
Fig. 36: Level of discrimination of river water height in the Santa Lucia middle basin during October and February
for the period 1979-2003 (from Caffera et al., 2004).
3.5.2 Trophic state
The evolution of the trophic state (TS) in the Santa Lucía river estuary showed a strong relationship
with both QU and QSL during the period October 2002 and May 2004. We selected one state / impact
48
variable of TS, chlorophyll-a, (Figure 38) to show this relationship, as well as the coping capacity
and vulnerability of the ecosystem to ENSO-related climate variability. During the studied period
the temperature control on TSC was moderately high (correlation-r T vs Chl-a: 0.44) but was almost
blocked during the peak of river flow – of both QU and QSL- from October 2002 to May 2003. Both,
the increases in freshwater in the RP and QSL enhanced physical controls on TSC other than
temperature: decrease in ft of water and plankton, increase in turbulence, and supression of the
estuarine circulation and stratification regime. This control blocked the expression of TS symptoms
when salinity was 1< and chl-a varied from 0 to 7 µg/L in the estuarine zone (Sgo. Vázquez) and
from 0 to 8 µg/L at the river - estuary boundary (Delta del Tigre). Once both QV and QSL were
within the coping range since October 2003, salinity increased to 4-7 as well as chl-a did up to
eutrophic levels (18-28 µg/L) at both stations.
Some concluding remarks of these observations are: i) during normal years the system expresses
symptoms of TSC which agree well with nitrate excess (30 - 70 µM), ii) during El Niño years the
system does not develop symptoms of TSC and deliver nutrients to the RP, and iii) during La Niña
years the system should be prone to increase TSC, as observed in the RP ( Nagy et al., 2002a,b).
Summarizing, fluctuations of river flow, which are partially ENSO-controlled, is a strong physical
control of biogeochemical processes and TSC of SL inducing enviromental shifts within this system
and in the adjacent coastal waters of the EF of the RP.
Evolution of Salinity and Chlorophyll at
Sgo. Vazquez, Santa Lucia river (102002 / 04-2004)
20
Evolution of Salinity and Cholorphyll at
Delta del Tigre, Santa Lucia river (10-02 /
04-2004)
18
16
30
14
25
12
20
10
8
15
6
10
4
5
2
0
0
10/02
01/03
04/03
07/03
Month/Year
10/03
S ppt
01/04
04/04
10/02
01/03 04/03
Clo. a ug/l
07/03
10/03 01/04
Month/YearS ppt
04/04
Clof. a ug/l
Fig. 37: Evolution of salinity and chlorophyll-a at Santiago Vázquez (estuary, left) and Delta del Tigre (riverestuary boundary, right) from October 2002 to May 2004 (from Caffera et al., 2004).
7
3.5.3 An Scenario for 2050
A plausible combined climatic scenario for 2050 could be:
•
+ 0.20 m SLR,
•
increase in SSE wind storm surges and precipitations,
•
a strong El Niño year (i.e. October-December), should increase both SLR and DRH,
blocking the discharge of QSL.
This scenario would ravage, erode and impact the coastal ecosystem, infrastructure, tourism,
fisheries and agriculture sectors, as well as coastal settlements on both the coast and SL river
49
margins. Thus, the regional vulnerability - coastal zone, water resources, coastal settlements and
fisheries livelihood sectors - are related.
50
4 Adaptation
4.1
Activities Conducted
The aim of this section is to present future adaptation (planned) strategies for the Coastal Fisheries
System. Current adaptive capacity and autonomous measures have been explained in the
vulnerability section. A deep understanding of the climate, cultural, economic, environmental, legal
and social constraints to adaptation would allow to improve the adaptive management and
sustainability of fish resources and livelihood of the associated coastal community of fishermen.
First of all we define the concept of adaption.
4.2
What is Adaption?
Adaption is the process by which stakeholders involved reduce the adverse effects of climate on
their livelihood. This Process involves any passive, reactive or anticipatory adjustment of behavior
and economic structure in order to increase sustainability and reduce vulnerability to climate
change, variability and weather / climate extremes (modified from Burton, 1996,1998,2000; Smith et
al., 1993; Smit et al., 1999).
4.3
How Does Adaptation Occur?
Through processes: External forcings (river flow and wind changes) induce displacement of the
frontal zone and variations in the location of main resource (Croaker), which ultimatley induced an
autonomous adaptation strategy (at the very beginning): seasonal or permanent fishermen
migration.
The former option of has being succesful until 2002.
Data used are those analyzed in the vulnerability section (vulnerability indicators and matrix) and
economic fishing activity estimation (see Table 5; Figures 26 and 27).
Based on these criteria, we propose an Adaption Control Information System (ACIS).
4.4
Scientific Methods and Data
Our methodological approach was based on: i) framework for vulnerability and adaptation for a
second generation assessment (SEI, 2001), ii) multi-level indicator of vulnerability to climate change
(Moss, 1999), iii) expert judgement, iv)cost-benefit analysis and regret options, v) Integrated Coastal
Zone Management and vi) adaptive management.
Adaptive management leaves scope for decisions to be reviewed, and further decisions
implemented at a series of later dates, as improved information becomes available on the nature of
the present day and future climate risk (Hillborn and Sibert, 1988; Hillborn and Peterman, 1996;
UKCIP, 2000).
4.5
Results
4.5.1 Migration adaptation strategy of artisanal fisheries
Spatial changes along the coast reduce the ability of fishermen to catch in other conditions
increasing their vulnerability to the vicissitudes of life relocating and finding employment outside
of fisheries (i.e. agriculture). However, fishermen don’t notice fluctuations of resources untill they
perceive changes of availability as a consecuence of river flow. Thus, extreme events drive adaptive
prevention of loss.
51
This autonomous seasonal migration strategy resulted in a planned definitive adaptation for many
fishermen which changed their location of housing and fishing activity (from Western Montevideo
and Santa Lucia river mouth to San Luis). These fishermen accepted the permanent loss of benefits
in order to avoid uncertainty and risks associated with the displacement of the estuarine front
driven by hydroclimatic fluctuations. Thus, accumulated loss over long-periods are minimal
regarding to benefits (low regret option).
4.5.2 Industrial Fisheries
The industrial fleet that operates – and compete with – the artisanal fleet is subject to changes in
resources and markets (Figure 38). However, because of its capacity to fish in open waters is less
dependent on climatic and weather constraints.
Change in resources use (other species)
Changes in technological aspects
Economics aspects (markets)
Fig. 38: Environmental, economic and technological adaptive management conditions of industrial fishery (from
Norbis, 2003).
4.5.3 Integrated Coastal Zone Management and Adaptation Control
Information System
Positive trends (last 30 years) in the Rio de la Plata basin and estuarine system imposes defies and
threatens to the CFS. The best options to deal with these trends are the development of an
Integrated Coastal Zone Management (ICZM) program which should prioriotize participatory
processes, education, weather and climatic forecasting, update of fisheries resources and water
quality, real-time information, early warning systems, and adaptive management options. Thus,
anticipatory measures are needed, because under strong climatic pressures fishermen are strongly
impacted, and reactive measures have poor results or can lead to mis-adaptation (as happened in
2002).
Because of uncertainty, management strategies should be periodically revised and adapted to the
dynamic conditions of the stock, environment and resource users, as well as to changes in the
intertemporal preferences of the fishing sector (Adaptive management).
Adaption measures will have positive impacts provided communications among stakeholders
(fishermen, managers, local authorities and scientists) are improved. Nor the acquired knowledge
neither the improve of knowledge, partial relations and communications will be enough until
managers and local authorities (i.e., Directorare of Aquatic Resources, Navy Coast Guard, Ministery
of Housing, Territorial Planning and Environment) take effective measures, and until fishermen be
able of making an effective use of knowledge, information and early warning. An important
constraint is the failure of fit between time and space scales between institutions (responsible for
management) and Actors (fisheries components). We propose a hierarchical procedure of
adaptation control information system (Figure 39) which tales into account most of the above
mentioned aspects.
52
HIERARCHICAL PROCEDURE OF Adaptation Control Information System
Stakeholders
Understand fishermen knowledge
Observation
changes
Evaluation and confirmation of trends
(monitoring)
and
knowledge
of
Researchers
Fishery, Marine, Social and
Environmental Scientists
Implementation of Policies
Early warning
Managers
Fig. 39: Hierarchical procedure of the adaption control information system - ACIS (modified from Norbis, 2003).
4.5.4 Scenarios of adaptation and sustainability
We have developed models of fishing activity based on observed data presented in Table 5, and
Figures 26 and 27. Observed data are: 923 boats sortied in 64 days with an average catch of 22
53
boxes. The model consider 640 boats sortied (10 boats per sortie/day) and an average catch of 20
boxes per sortie/day.
Figure 40 shows the comparison between observed Vs modeled total accumulated boxes. Up to ~50
fishing sorties (days), observed capture is greater than modeled capture, whereas for fishing sorties
greater than 50 modelled captures are greater. For instance, for 64 sorties, the increase in capture
should be about 60%.
Fig. 40: Figure Comparison between observed Vs modeled total accumulated boxes.
Figure 41 shows three scenarios as a function of sortied days.
•
Scenario 1 (blue):
31 average boxes and 15 boats.
•
Scenario 2 (pink):
Fishing period 1998-199.
•
Scenario 3 (yellow):
40 average boxes and 31 boats.
Scenario 3 is the maximum expected capture under ideal – but plausible – conditions. Scenarios 1
and 2 do not give differnet captures for a number of sorties greater than 50.
54
Fig. 41: Fishing scenarios: Capture (log of boxes) as a function of sortied days.
4.6
Conclusions
Modeled scenarios, which take into account cautious numbers of catch per day, suggest that an
increase in the number of sorties is the key factor.
Thus, if nor weather neither climate conditions can be managed, real time forecasting and
communication with fishermen, which should allow to increase the number of sorties under good
fishing conditions, seem to be a good adaptation practice. For this, an increase in security of
navigation and relations with the Coast Guard is needed.
Average boxes and sortied days are not independent. Evidence is that when fishing conditions are
better, more fishermen decide to fish. Usually a few number of performant fishermen decide to fish,
and this number should increase if adaptation measures are taken.
Thus, a plausible combination of an increase in the number of sorites and average box capture
should be the most realistic scenario to increase fishermen’s net income in order to recover the
investment capital.
The hierarchical procedure of Adaption Control Information System is suggested as an example of
adaptive management.
Current and future adaptation strategies of coastal fishermen are climate influenced decisions, it is
to say that climatic factors prevail over non-climate decisions, taking into acocunt a low regret cost
– benefit ratio.
55
5 Expected future climatic and environmental scenarios,
impacts and vulnerability
5.1
Implications for Estuarine Biocomplexity.
The following paragraphs drown from the report: Summary of Climate Change Assessments:
Implications for Estuarine Biocomplexity (Boesch, 2002), seems to be a likely scenario for most
temperate estuaries, such as the Rio de la Plata.
“In estuaries and coastal waters experiencing seasonal density stratification, climatic conditions
projected for later in the 21st century could bring earlier, longer lasting and stronger stratification
affecting nutrient and oxygen dynamics, changes in the dominant phytoplankton competing for
available nutrients and subsequent effects on higher trophic levels and microbial remineralization
processes”
It stands to reason that a warmer Earth will bring more overall precipitation because rising
temperatures will increase evaporation and accelerate the water cycle. However, just as there are
deserts and rainforests, this does not mean that precipitation will increase everywhere—if fact,
models project that some regions may receive less precipitation. Furthermore, precipitation is more
greatly influenced by regional—even local—processes than temperature, reducing the confidence
one can assign to projections of changes in precipitation falling on or runoff delivered to a specific
estuary.
GCM models often produce widely different projections of changes in precipitation on regional
scales and their results should be interpreted with caution. Nonetheless, the models generally agree
on two things: changes in precipitation in a specific area are likely (although how much and even
the sign of the change may be uncertain) and the frequency of heavy precipitation events is likely to
increase.
5.1.1 Temperature
According to the IPCC the following climate changes are very likely over most areas during the 21st
century: higher maximum temperatures and more hot days; higher minimum temperatures, fewer
cold days and frost days; reduced diurnal temperature range; increase in the heat index (combining
temperature and humidity); and more intense recipitation events. Likely changes include: increased
summer drying and associated risk of drought. Based on GCM models, the average global
temperature is projected to increase by 1.4 to 5.8ºC by the end of the 21st century, with a most
probable increase of 2-4ºC. Temperatures are projected to rise more rapidly (IPCC, 2001).
5.1.2 Climate change implications after about 2040.
While a change of a few degrees might not seem like much, it should be remembered that this is an
annual and global average. Put in proper context, the projected global mean temperature would
greatly exceed the range of variability within the last 1,000 years and the rate of warming is without
precedent during the past 10,000 years, based on paleoclimate data.
5.1.3 Climate change implications
The effects of these changes in air temperature on water temperature in estuaries are not
straightforward. Water temperatures in east and Gulf coast estuaries that have a small tidal prism
(such as the RP) are fairly closely linked with air temperature rather than the temperature of the
coastal ocean. Of course, this varies with respect to distance to the mouth of the estuary. In any
case, milder winter temperatures and warmer summer temperatures, plus changes in the seasonal
56
timing of temperature would have manifold consequences to estuarine ecosystems, including, but
not necessarily limited to (only retained those which could occur in the RP):
•
high temperature stress on indigenous biota;
•
increased metabolic rates;
•
opportunities for invasive species currently limited by minimum temperatures;
•
earlier warming and later cooling, with effects on production cycles, seasonal timing;
•
lowered summer dissolved oxygen levels because of higher temperatures;
•
stronger density stratification, with effects on oxygen, circulation, and biogeochemical
processes.
5.2 Future Regional Climate Scenarios and Expected
Environmental Impacts and Vulnerability.
5.2.1 Regional climate scenarios for Southeastern South America.
In order to evaluate the differences between the observed climate and the climate simulations with
Global Climate Models (GCMs), in the Southeastern South America region, we selected seven
available runs from IPCC Distribution Data Center, using socioeconomic SRES-A2 and B2 forcing
scenario. The models are: HadCM3, ECHAM4/OPYC3, CGCM2, NCAR-PCM1, GFDL R30, CSIRO
Mark 2 and L8-LMD.
We have compared sea level pressure, surface air temperature (Figure 41) and precipitation (Figure
43) from the models, against observed climate fields, trying to estimate regional performance of the
control simulations (baseline climate scenarios). We assume that the models that better simulate the
current regional climate in their control experiments are likely to be more reliable in their
simulations of regional climate under changes of greenhouse gases concentrations.
The comparison between the monthly and annual SLP fields shows that only four models
(HADCM3, CSIRO-mk2, ECHAM4, GFDL-R30) have an acceptable agreement with the observed
SLP field and are able to represent the position and intensity of the pressure systems and the annual
cycle. Comparison for precipitation was performed only for the four models with best agreement in
the SLP fields: HADCM3, ECHAM4/OPYC3, CSIRO-mk2 and GFDL-R30. In all cases, precipitation
is largely underestimated in the Río de la Plata basin. The comparison between the monthly and
annual temperature fields shows that in general all the models have an acceptable agreement with
the observed fields.
We used the original spatial resolution of both models: HadCM3 has an horizontal resolution of
2.5° of latitude by 3.75° of longitude. The model ECHAM4 has an horizontal resolution of 2.8° of
latitude by 2.8° of longitude. The future climate change scenarios, for precipitation and
temperature, over Southern cone of South America were constructed for 2020, 2050 and 2080s. Only
as example the figure shows the changes in precipitation for 2050 and 2080 over the south of South
America, estimated by HADCM3 model forced by SRES A2 socioeconomic scenario.
57
SLP (hPa)
ECHAM4 ANUAL (PERIODO 2000-2050)
-20.00
-25.00
-30.00
-35.00
-40.00
-45.00
-65.00
-60.00
-55.00
-50.00
-45.00
Fig. 42: Future changes (2050) in Sea level pressure (above), and temperature (below) for RPB.
58
2050 SRES-A2a
Fig. 43: Future scenarios for precipitation (SRES-A2a) for 2050 (above) and 2080 (below).
2080 SRES-A2a
59
5.2.2 Statistical and dynamical downscaling experiments.
In order to generate precipitation and temperature daily time series based on future climate change
scenarios from the Global Climate Models (GCMs) we selected the both statistical and dynamical
techniques for downscaling. Because of the coarse resolution of GCMs, downscaling techniques are
used to bridge the spatial and temporal resolution gaps between what climate modelers are
currently able to provide and what studies impact and vulnerability assessments require. We make
use of statistical downscaling technique through the SDSM model (Wilby et al, 2001). With the goal
of determinate the performance of daily rainfall prediction with SDSM model, we selected predictor
variables.
The selected ones for daily precipitation are sea level pressure, zonal and meridian wind
components at 850 hPa. This daily variables was selected because their strongly correlation with
observed precipitation at surface and are accurately described by the GCMs. The predictor
variables came from the reanalysis (Kalnay, E. et al, 1996), of National Centers for Environmental
Prediction (NCEP. We selected four locations in Southeastern South America during the period
1996 – 2001. The cities are Buenos Aires and Santa Fe in Argentina, and Montevideo and Salto in
Uruguay. As final conclusion we have that statistical downscaling SDSM model is a valuable tool
and is capable of representing many of the characteristics that existed in the precipitation data of
the temperate region of South America.
Another tool used, at the end of AIACC project, to generate future high resolution scenarios over
Southeastern South America was PRECIS. This is based on the Hadley Center’s regional climate
modeling system. It has been ported to run on a PC (under Linux) with a simple user interface, so
that experiments can easily be set up over any region. PRECIS was developed in order to help
generate high-resolution climate change information for as many regions of the world as possible.
The PRECIS was transferred freely to Faculty of Sciences in Uruguay, to help to develop climatechange scenarios at national scale and simultaneously building capacity and drawing on local
climatological expertise. These scenarios will be used in impact, vulnerability and adaptation
studies, and to aid in the preparation of National Communications behalf Unit of Climate Change
(Ministry of Environment).
5.2.3 Some conjectures about future climatic scenarios and associated
environmental vulnerability and impacts.
In additon to the scenario developed by Boesch (2002) for the Estuaries of the United States, which is
generally valid for most temperate estuaries all over the world, we make some assumptions,
conjectures, primary conclusions and questions about the RdlP basin, esutary and coast, which as a
whole, may be considered as work hypothesis for future research.
Current environmental scenarios (1971-2003) in the Rio de la Plata basin (RPB) and estuary (RP)
discussed all along this report are dominated by the following main stresses:
•
increases in temperature, precipitation, streamflow and onshore winds.
•
increases in population, use of natural resources and export of nutrients.
•
increases in economic activities, land use changes, soil erosion and runoff / infiltration
ratio, damming.
Current climate and future scenarios (time horizon 2020 - 2050) for the RPB and RP suggest a
change in precipitation, temeperature and sea-level rise within the ranges 5% - 10%, +1 to +2°C and
+ 10-20 cm respectively. During the last few decades these changes have being + 20 - 25% for
precipitation, +0.6 - +0.9°C for temperature and 5 cm for sea-level rise, as well as + 25 - 40% for
river flows (AIACC LA-32, 2005).
Trends for QVs are very difficult to be estimated because of both the uncertainty of regional human
drivers (i.e., land-use change and runoff / infiltration ratio) and because of the varied regional
scenarios from different GCMs. For precipitation, all of them have systematically underestimated
the precipitation over the region, but not necessarily the increase of it. Indeed, during the past few
decades the observed increase in precipitation (Liebmann, 2004) was associated with the observed
60
increase in riverflow. Moreover, small changes in precipitation are doubled in the streamflow signal
(Berbery and Barros, 2002). Tucci and Clarke (1998) suggested that 1/3 of observed increases in
streamflows were attributable to land use changes.
From an environmental point of view, under a future scenario (2020-2050) in which streamflow
remains similar or slightly lower (i.e. 0% to -10%) with regard to present values, we do not expect a
significative increase in current environmental stresses on the estuarine system (which are already
moderately high) with the expection of N inputs and further TSC.
Our concern is about a future scenario where QV increases within the range ~ 10-25%, together with
projected temperature increases, economic and population growth, for which significative impacts
are expected in the estuarine and coastal systems (i.e., increase in the vulnerability to TSC, and airwater and sediment-water gases, and nutrient exchanges) besides changes in the shelf and contour
current circulation (i.e., water temperature changes; ocean-driven HABs; see Figure 14).
Thus, the following key question arises:
•
Is the increase in both temperature and QV plausible under projected changes in
temperature (i.e.+ 1-2° C) and precipitation (~5-10%), taking into account the consequent
increase in evapotranspiration?
Some assumptions are:
•
about 1/3 of QV changes may be due to land use changes (Tucci and Clarke, 1998).
•
observed vs. projected changes are of the same sign in all variables,
•
the expected value for temperature change is 2 to 4 times greater than the formerly
observed.
SLR rate will accelerate (with regard to the rate prior to 1990).
Main uncertainty is related to the relative amounts of potential and actual evapotranspiration rates
in the future, which makes very difficult to establish any coherent scenario about future
streamflow, especially if current land-use changes continue increasing the runoff / infiltration ratio
(which could reduce the impact of temperature rise on evapotranspiration).
Considering the fact that seasonal temperature, precipitation and streamflow cycles are not
superposed, any changes should modify seasonal circulation and mixing status, inducing further
environmental shifts (i.e. gas and nutrient exchanges, ∆ P-R, increase in HABs occurrence, with a
probable increase in both the degree and occurrence of hypoxic events (estimated to be about - 20%)
in deep bottom waters and denitrification (emission of N2 / N20 to the atmosphere; Nagy et al.,
2002a,b; 2003), as well as an increase in the vulnerability of fishermen communities and low-lying
areas.
The long-term evolution of salinity (Nagy et al., 2002a; Bidegain et al., 2004) and its monthly
evolution during the period 1998-2002 (Nagy et al., 2003; Severov et al, 2004), as well as the
fluctuations of the estuarine fronts location within the RP and adjacent shelf since 1998 (Severov et
al., 2003. 2004; Nagy et al, submitted) allows to develop a conceptual model - not detailed here - on
both yearly and monthly basis (see Figure 12):
•
when QU was/is 4,000 m3/s, typical yearly salinities were/are >10-12,
•
when QU was/is >5,500 m3/s they are ~7-9 (present average: ~8),
•
when QU was/is >7,000 m3/s salinity is <5 on timescales greater than weather
development,
•
when QU is> 10,000 m3/s freshwater prevail in most of the Uruguayan coast and the EF is
displaced tens of miles to the mouth.
Under a hypothetical environmental scenario for 2020 - 2050, based upon climate models outputs,
past trends, reference projections and expert judgment, some speculations can be made.
61
Both long-term and monthly analysis of recent years allow to suggest that a hypothetical increase in
QU of ~ 20% should reduce average salinity at Montevideo by 2-3 (reaching 5-6) and displace
riverward the EF. If these changes are coupled with a plausible increase in onshore winds,
especially during spring and early summer months - when ENSO is active and biological processes
and goods are in their activity peak period - significant changes in both the structure and location of
the several fronts of the RP - as well as of the biological and biogeochemical functions associated,
including fish reproduction, fishing activity and gas dynamics, are expected to shift (Severov et al.,
2004; Nagy 2004; Lappo et al., 2005; López and Nagy, 2005; Nagy et al, submitted).
The export scenario (delivery to the coastal ocean) of N for South America for the year 2050 would
increase nearly three times. Generically, the temperate regions export less than half N from total
anthropogenic sources than tropical regions do, which is partially explained by lower precipitation
(Seitzinger et al., 2002). Thus, ENSO variability plays a major role as a control factor of drivers,
control and state variables of TSC in the RdlP (Nagy et al., 2003, 2004).
Under conditions of a moderate and combined increase in temperature, QV, QN and p in this period,
the occurrence of extreme climatic events (e.g. El Niño 1997-1998; Nagy et al., 2003a), could increase
the frequency of hypoxia and so affect eggs and larvae, thus increasing the vulnerability of adults to
other stress factors and even causing them to move away from the present area of capture, reducing
the income of coastal fishing communities.
Some expected impacts and responses under current (1980-1990) and future scenarios (2025-2050)
should be an increase in algal biomass, HABs events, changes in nutrient ratios (i.e. > N/P and
N/Si) – the three of which have been already observed in the last decade -, hypoxia, a decrease in PR balance and changes in biodiversity.
Projected or estimated scenarios of human drivers (i.e., + 70-100% population, > ~150-200% N
input; Nagy et al., 2003) - as well as some further land-use changes - for the URB are to be accounted.
Then, significant changes in symptoms of eutrophication and coastal fisheries livelihood are
expected. The former should be noxious for both the environmental and human health, as well as
for fisheries. The latter should modify the timing and quantities of ecological processes and services
and could make unsustainable coastal fisheries by reducing the number of days per month and the
months favorable for fishing activity.
The export scenario of N for South America for the year 2050 would increase nearly three times.
Generically, the temperate regions export less than half N from total anthropogenic sources than
tropical regions do, which is partially explained by lower precipitation (Seitzinger et al., 2002). Thus,
ENSO variability plays a major role as a control factor of drivers, control and state variables of TSC
in the RdlP (Nagy et al., 2003, 2004).
Under conditions of a moderate and combined increase in temperature, QV, QN and p in this period,
the occurrence of extreme climatic events (e.g. El Niño 1997-1998; Nagy et al., 2003a), could increase
the frequency of hypoxia and so affect eggs and larvae, thus increasing the vulnerability of adults to
other stress factors and even causing them to move away from the present area of capture, reducing
the income of coastal fishing communities.
Some expected impacts and responses under current (1980-1990) and future scenarios (2025-2050)
should be an increase in algal biomass, HABs events, changes in nutrient ratios (i.e. > N/P and
N/Si) – the three of which have been already observed in the last decade -, hypoxia, a decrease in PR balance and changes in biodiversity.
Summarizing, eutrophication in the Rio de la Plata system can be thought of as a syndrome (a suite
of symptoms) that change with the seasons, years and decades, showing an increasing trend of
pressure and state indicators since the mid 1940s, and a shift during the 1970s and 1980s. Natural
processes must have been accelerated due to the increase in hydroclimatic means and extremes that
led to an increase in soil erosion and diffuse sources of nutrients. These processes, combined with
human activities such as damming, which have indirectly altered the trophic status by modifying
the physical environment (e.g., residence time, local warming), determine that the increase in
nutrient load over the last five decades, even if it was well below the figures for developed
countries, has altered the natural trophic status background and/or stimulated the development of
new symptoms, whose drivers are expected to increase (since 1990) in the next few decades
(modified from López and Nagy 2005).
62
It must be emphasized that because of the particular dependence of SLR in the RP on non-eustatic
factors (sea level pressure, river flow and winds), further changes in the three of them under the
minimum SLR projections (i.e. only 0.20-0.30 m), are a potential threat to the coastal system
provided past synoptic and climatic extreme events occur simultaneously, which has already
happen.
Taking into account the evolution, variability and extremes of temperature, precipitations, sea level
rise, winds, river flow and trophic state variables change during the last 30 years over the Rio de la
Plata basin and estuary and the acceleration rates of change of most of them during the last 10
years, we are in need to assume a pessimist point of view.
Human drivers (increase in population density, damming and agricultural intensification), and
climatic change and variability (CCV) within the lower basin of the Rio de la Plata (shown for
Rivers Uruguay, Negro and tidal freshwater of the RdlP) are schamatized in in Tables 16 and 17.
Projecting these recent changes through the next 10-30 years, together with a plausible extreme
future scenarios for temperature and streamflow, significant environmental changes, shifts and
impacts are to be expected (i.e., increase in all symtoms of eutrophication, loss of area and / or
function of coastal wetlands, and decrease in coastal fisheries income and sustainability).
63
Table 16: Global accumulative, systemic and ENSO-related climatic and environmental changes in the Rio de
la Plata basin and Estuary.
64
Site/
Period
1- 1925-33
2- 1934-45
3- 1946-1980 4- 1981-2000
5- 2000-2004 620202050
Drivers
and
Trophic
status
and
change
Pristine baseline
(low
PD,
absence of dams
and
fertilizer
application).
Developme
ntof HDof
TSC
(Damming)
Increase in
HD
(damming,
agricultural
intensificati
onand PD)
and
symptoms
of TSC.
Consolidation of HD
and
CCV
drivers
of
TSC
and
symptoms.
Acce leration
of
CCV
(precipitation,
temperature)
and of HD of
TSC
C-HABs.
Oligomesotroph
ic
Mesotrophic Mesotrophic Mesoeutrophi
c
Moderate
increases
in PD and
temperature, and
high
increase
in
N
export.
Mesoeutrophic to Eutrophic
Eutrophic
Lower
First records of No data
Basin of cyanobacteriae
the RdlP in Uruguay
Constructio
n of Rincón
(in River
del Bonete
Uruguay
Dam
)
(1945)
Constructio
nof
Baygorria
Dam (1962).
Strong
increase in
population
and
beginning of
the use of
fertilizers
Construction
of
Salto
Grande-SG R.
Uruguay,
1979)
and
Palmar
(R.
Negro, 1982)
dams.
Increase
in
agricultural
intensification
.C-HABs
in
SG Dam
C-HABs in
Dam
reservoirs
of
Rivers
Negro and
Uruguay
(M.
aeruginosa)
Expected
increase
in
nutrients,
chl-a, and
C-HABs,
Tidal
river and
estuarine
front of
the Rio
de
la
Plata
Blooms
of
eutrophic
environmen
t diatoms in
R.Uruguay
and
other
streams (in
the 70s).
Blooms
of
M.aeruginosa
in the tidal
river of the
RdlP all along
the year, and
C-HABs
during
summer and
fall
Recurrent
yearly
CyanoHABs,
especially
during
summer
and
fall.
Increases in
nutrient
and
algal
biomass
concentrations
Increaae
in
all
variables
of
pressures
and state,
and
symptoms
of TSC up
to
eutrophic
levels.
Absence of C- Booms
of
HABs
blooms Microcystisi
(Microcystis,
n summer.
Anabaena,
Aphanizomeno
n)
Table 17: Past, current and future scenarios of trophic state expressed by Cyanobacterial Harmful Algal
Blooms (C-HABs). Six periods are defined, from baseline (1) to a plausible future scenario for 2020-50 (6)
(modified from López and Nagy, 2005).
65
6 Overall Concluding Remarks
The overall vulnerability and associated impacts on estuarine waters, goods, processes and services,
and coastal zone of the Uruguayan coast of the Rio de la Plata is primarily associated with ENSOrelated climate variability.
In addition, human and climatic changes are drivers of environmental pressure and state variables
within the RP basin and sub-basins at different spatial- and time-scales, which produce, stimulate
or triggers impacts, ecosystem responses and shifts within the estuarine waters of the RP and its
coastal zone.
Increase in precipitation plays a major role in controlling buoyancy and stability, nutrient export,
eutrophication and P-R processes, since sensitivity to trophic state changes depends on the balance
between river flow and winds.
Streamflow variability of the Santa Lucía River is ENSO-related from August/October to
December/February. Therefore, an increase of this variability under a SLR scenario > 0.30 m should
seriously impact the system by flooding the lower basin plain, estuary and coastal zone in the shortand mid-term (2020 - 2050). This woul also affect the contiguous estuarine front.
Projected estimated scenarios for 2050: [+ 1-2º C, + 5 - +20% precipitations,+ ~70% inhabitants, +
~200% Nitrogen, + 0.3-0.5 m SLR, + ~15-25% river flow; -2 in surface salinity, + ~100% nutrients, ~20 % oxygen saturation in bottom waters, - ~25% net income of coastal fisheries], will increase
vulnerabilities of the exposed sectors and some of them will be heavily impacted, threatened
and/or will be unsustainable (coastal fisheries, low-lying wetlands and beaches, tourism, supply of
drinking water).
Further increase in the Santa Lucia river flow could change the river morphology as well as the
capacity of its wetlands to retain floodings. This could impact the built infrastructure (i.e. bridges
and roads) designed under past hydrological statistics, as well as affect the trophic status.
Climatic changes (QV and W) should modify the circulation, stratification and mixing status
inducing further environmental impacts (i.e., ∆ P-R, oxygen status, HABs, increase in the
vulnerability of fishermen and low-lying areas).
Hopefully, recent public initiatives on prospective analysis of coastal systems, including the
biophysical and human dimensions of climate change and variability, as well as the 3rd National
Communication to the UNFCC could take into account some of these conclusions.
66
7 Capacity Building Outcomes and Remaining Needs
Capacity building was second to none among AIACC LA-32 priorities. In most cases capacities
were applied in specific activities. However, we put the emphasis on long-term development and
science-policy linkages.
7.1
Capacity Building
Several junior and senior researchers involved in AIACC LA-32 got acquainted with new
knowledge, skills and techniques by attending to workshops and courses, as well as in-hand
activities.
For instance:
Mario Bidegain attended to the AIACC workshop on Climate Scenarios in Norwich, UK, 2002.
GJ Nagy, A Ponce and G Sención attended to the AIACC Workshop on Vulnerability and Adaptation
in Trieste, Italy (2002).
Alvaro Ponce and Juan Lagomarsino attended to a GIS and Environmental Analysis course at the
University of Buenos Aires, Argentina (2003).
Roberto Silva and Alvaro Ponce attended to courses on Participatory Processes organized by Project
Eco-Plata (2004).
Karina Sans and Juan Lagomarsino attended to a Graduate course on Estuarine Systems (2004).
César López attended to a course on Coastal Wetlands Management (2004).
César López attended to a graduate course on Remote Sensing of Oceans at the University of
Concepción, Chile (2004).
Mario Bidegain and Juan Lagomarsino attended to the “Precis Training Workshop” in Sao Paulo,
Brazil, November, 2004.
Several senior researchers involved in AIACC LA-32 developed lectures, modules and courses for
undergraduate and graduate students, as well as for High School teachers.
C Martínez, M Bidegain, GJ Nagy and RM Caffera developed lectures on Global Change for a course
on Earth System Science devoted to High School teachers of Earth and Space Sciences.
GJ Nagy and M Bidegain developed lectures on Global Change for a Graduate International course
on Ocean Color for Latin American students.
GJ Nagy, M Bidegain, RM Caffera and A Ponce updated the course on Earth System Science and
Global Change for the Master of Science in Env. Sciences, Facultad de Ciencias, UdelaR.
RM Caffera, M Bidegain and GJ Nagy presented project’s results in several outreach-type meetings
organized by the Ministry of the Environment (2005).
Advice and financial support was given to Alvaro Ponce to perform his research on Global
Environmental Change of the Santa Catalina coastal site (IIASA-START Grant).
7.2
Remaining Needs
In spite of the above mentioned activities and the continuous learning process associated with
research we detect a partial lack of capacitites in some fields such as:
•
Vulnerability mapping.
67
•
Integrated climatic, environmental and socioeconomic analysis.
•
Quantitative multicriteria assessments of stakeholders perception
•
Particpatory processes and stakeholders engagement.
We assume that Integrated climatic, environmental and socioeconomic analysis will be performed
by the economist who will participate in the 3rd National Communication in collaboration with our
AIACC-team.
68
8 National Communications, Science-Policy Linkages and
Stakeholder Engagement
Capacity Building, Science-Policy Linkages and Stakeholder engagement were mainly directed to
strengthen relations with government agencies. AIACC LA-32 was invited by the Unit of Climate
Change and GEF-related projects (FREPLATA), to participate in their activities. Outputs of these
activities were part of / or complemented the initial goals of AIACC by 2001.
Relevant examples are:
•
Researchers from LA 32 AIACC LA 32 participated in the revision of the 2nd National
Communication (SNC) Draft under the UNFCC.
•
Researchers from LA 32 AIACC LA 32 participated in several workshops (2003-2005)
organized by the Ministry of the Environment (i.e,. Synergies of the three international
conventions: Biodiversity, Climate Change and Desertification.
•
G J Nagy was nomitated by the IPCC to act as a Lead Author of Chapter 13 (Working
Group II, Latin America – coasts). He was supported by the Directorate of the Environment
of the Uruguayan Ministry of Foreign Affairs, the Unit of Climate Change of the
Uruguayan Ministry of the Environment and AIACC.
•
Researchers from LA 32 LA 32 participated in a series of 4 Prospective workshops
organized by the Minisitry of the Environment: “Reflections on Uruguay 2025” (Coastal
Zone + River Uruguay margin Working Group).
•
Researchers from LA 32 were engaged by the Ministry of the Environment to update
climatic, hydrologic and oceanographic trends in order to prepare the 3rd National
Communication (TNC) under the UNFCC.
•
GJ Nagy and R. M. Caffera attended to a LA-26 stakeholders meeting in Buenos Aires (July,
2004).
•
GJ Nagy was invited to present a draft on coastal systems and to explain to the GEF
consultant the capacity to undertake vulnerability and adaptation assessments for the
coastal systems, fresh and estuarine waters during the TNC.
69
9 Policy Implications and Future Directions
AIACC LA-32 was succesful in some subjects that have policy implications: Interaction with
government agencies and international projects, outreach and public awareness, supported
scientific activities of a memorandum of understanding with the Russian Academy of Sciences. We
must emphasize the fact that our team is consulted by some government agencies and journalists
on climate variability, change and extremes. Future direction of our team seems to be related to
environmental and climatic emergencies, development of early warning systems and adaptation
policies.
Some examples are:
•
AIACC LA-32 developed cooperation with the Directorates for Water Resources (Min. of
Public Works) and Hydrography and Oceanography (Min.of Defence), the Public system of
education (elementary, high and technical schools) and the Russian Academy of Sciences
(Institute of Oceanology).
•
LA 32 team members were invited by CONAMA (Perú) to act as consultatants of the
Peruvian Report on Vulnerability to Climate Change (2005).
•
LA 32 team members presented – together with other regional AIACC teams - a pre- and
full proposal on Global Change and Sustainable Livelihood in the Rio de la Plata Basin (IAI CRNII call).
•
LA 32 team members were invited by the Bi-National (Argentina – Uruguay) Uruguay
river Management Committee to present regional current and future climate and
environmntal scenarios. Agreements and specific activities -some of them associated with
adaptation policies- are expected.
•
LA 32 team members presented their results to NGOs, journalists and congressmen
(Environment Committee) in the Congress Building. We expect this should increase global
change awareness among some journalists and elected officials.
70
10 Published and Submitted Papers
Published
Lappo SS, E Morozov, DN Severov, AV Sokov, AA Kluivitkin, G Nagy (2005). In Russian. Frontal
Mixing of Fresh and Marine Waters in the Rio de la Plata. Transactions (Doklady) of the Russian
Academy of Sciences/Earth Science Section, 401 (2): 226-228.
Doklady of RAS, Earth Science Section, 2005, V 401, N2.
http://library.iem.ac.ru/dan/d-es/2-40105.html.
Submitted
Nagy GJ, DN Severov, V Pshennikov, M De los Santos, JJ Lagomarsino, K Sans, EG Morozov
(submitted to JASR). Rio de la Plata Estuarine System I: Relationship between River Flow and
Frontal Variability, Journal of Advance in Space Research, Elsevier.
Submissions Being Processed for Author Gustavo Juan Nagy, PhD
Action
Manuscript
Number
JASR-D-04View Submission
01223
Title
Rio de la Plata System: 1.
Relationship between River
Flow and Frontal
Variability. A2.1-0074-04
71
Initial
Date
Submitted
Status
Date
04.01.2005
19.07.2005
Current
Status
Under
Review
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